Overview

Dataset statistics

Number of variables463
Number of observations440
Missing cells167873
Missing cells (%)82.4%
Total size in memory8.5 MiB
Average record size in memory19.7 KiB

Variable types

Numeric1
Text335
Unsupported127

Alerts

school_10th_seats has constant value ""Constant
shared_space has constant value ""Constant
girls has constant value ""Constant
boys has constant value ""Constant
pbat has constant value ""Constant
international has constant value ""Constant
specialized has constant value ""Constant
transfer has constant value ""Constant
ptech has constant value ""Constant
earlycollege has constant value ""Constant
school_accessibility_description has constant value ""Constant
prgdesc10 has constant value ""Constant
directions5 has constant value ""Constant
directions6 has constant value ""Constant
directions7 has constant value ""Constant
requirement2_8 has constant value ""Constant
requirement3_8 has constant value ""Constant
requirement5_6 has constant value ""Constant
requirement5_7 has constant value ""Constant
requirement6_7 has constant value ""Constant
offer_rate8 has constant value ""Constant
offer_rate9 has constant value ""Constant
program10 has constant value ""Constant
code10 has constant value ""Constant
interest10 has constant value ""Constant
method10 has constant value ""Constant
seats9ge9 has constant value ""Constant
grade9gefilledflag9 has constant value ""Constant
grade9geapplicants9 has constant value ""Constant
seats9swd9 has constant value ""Constant
grade9swdfilledflag9 has constant value ""Constant
grade9swdapplicants9 has constant value ""Constant
seats2specialized has constant value ""Constant
seats3specialized has constant value ""Constant
seats4specialized has constant value ""Constant
seats5specialized has constant value ""Constant
seats6specialized has constant value ""Constant
applicants2specialized has constant value ""Constant
applicants3specialized has constant value ""Constant
applicants4specialized has constant value ""Constant
applicants5specialized has constant value ""Constant
applicants6specialized has constant value ""Constant
appperseat2specialized has constant value ""Constant
appperseat3specialized has constant value ""Constant
appperseat4specialized has constant value ""Constant
appperseat5specialized has constant value ""Constant
appperseat6specialized has constant value ""Constant
seats1010 has constant value ""Constant
admissionspriority110 has constant value ""Constant
admissionspriority29 has constant value ""Constant
admissionspriority35 has constant value ""Constant
admissionspriority36 has constant value ""Constant
admissionspriority37 has constant value ""Constant
admissionspriority46 has constant value ""Constant
admissionspriority53 has constant value ""Constant
admissionspriority54 has constant value ""Constant
admissionspriority56 has constant value ""Constant
admissionspriority62 has constant value ""Constant
admissionspriority63 has constant value ""Constant
admissionspriority64 has constant value ""Constant
admissionspriority71 has constant value ""Constant
admissionspriority74 has constant value ""Constant
eligibility7 has constant value ""Constant
common_audition1 has constant value ""Constant
common_audition2 has constant value ""Constant
common_audition3 has constant value ""Constant
common_audition4 has constant value ""Constant
common_audition5 has constant value ""Constant
common_audition6 has constant value ""Constant
common_audition7 has constant value ""Constant
grade9geapplicantsperseat9 has constant value ""Constant
grade9swdapplicantsperseat9 has constant value ""Constant
state_code has constant value ""Constant
school_10th_seats has 137 (31.1%) missing valuesMissing
academicopportunities2 has 17 (3.9%) missing valuesMissing
academicopportunities3 has 58 (13.2%) missing valuesMissing
academicopportunities4 has 128 (29.1%) missing valuesMissing
academicopportunities5 has 257 (58.4%) missing valuesMissing
language_classes has 18 (4.1%) missing valuesMissing
advancedplacement_courses has 121 (27.5%) missing valuesMissing
diplomaendorsements has 323 (73.4%) missing valuesMissing
shared_space has 70 (15.9%) missing valuesMissing
campus_name has 242 (55.0%) missing valuesMissing
school_email has 28 (6.4%) missing valuesMissing
subway has 79 (18.0%) missing valuesMissing
start_time has 9 (2.0%) missing valuesMissing
end_time has 9 (2.0%) missing valuesMissing
addtl_info1 has 142 (32.3%) missing valuesMissing
psal_sports_boys has 28 (6.4%) missing valuesMissing
psal_sports_girls has 35 (8.0%) missing valuesMissing
psal_sports_coed has 262 (59.5%) missing valuesMissing
school_sports has 138 (31.4%) missing valuesMissing
graduation_rate has 57 (13.0%) missing valuesMissing
college_career_rate has 71 (16.1%) missing valuesMissing
girls has 431 (98.0%) missing valuesMissing
boys has 436 (99.1%) missing valuesMissing
pbat has 402 (91.4%) missing valuesMissing
international has 418 (95.0%) missing valuesMissing
specialized has 431 (98.0%) missing valuesMissing
transfer has 429 (97.5%) missing valuesMissing
ptech has 433 (98.4%) missing valuesMissing
earlycollege has 421 (95.7%) missing valuesMissing
geoeligibility has 427 (97.0%) missing valuesMissing
school_accessibility_description has 114 (25.9%) missing valuesMissing
prgdesc1 has 232 (52.7%) missing valuesMissing
prgdesc2 has 320 (72.7%) missing valuesMissing
prgdesc3 has 370 (84.1%) missing valuesMissing
prgdesc4 has 390 (88.6%) missing valuesMissing
prgdesc5 has 406 (92.3%) missing valuesMissing
prgdesc6 has 418 (95.0%) missing valuesMissing
prgdesc7 has 429 (97.5%) missing valuesMissing
prgdesc8 has 435 (98.9%) missing valuesMissing
prgdesc9 has 438 (99.5%) missing valuesMissing
prgdesc10 has 439 (99.8%) missing valuesMissing
directions1 has 401 (91.1%) missing valuesMissing
directions2 has 431 (98.0%) missing valuesMissing
directions3 has 436 (99.1%) missing valuesMissing
directions4 has 437 (99.3%) missing valuesMissing
directions5 has 439 (99.8%) missing valuesMissing
directions6 has 439 (99.8%) missing valuesMissing
directions7 has 439 (99.8%) missing valuesMissing
directions8 has 440 (100.0%) missing valuesMissing
directions9 has 440 (100.0%) missing valuesMissing
directions10 has 440 (100.0%) missing valuesMissing
requirement1_1 has 316 (71.8%) missing valuesMissing
requirement1_2 has 383 (87.0%) missing valuesMissing
requirement1_3 has 397 (90.2%) missing valuesMissing
requirement1_4 has 405 (92.0%) missing valuesMissing
requirement1_5 has 417 (94.8%) missing valuesMissing
requirement1_6 has 426 (96.8%) missing valuesMissing
requirement1_7 has 433 (98.4%) missing valuesMissing
requirement1_8 has 438 (99.5%) missing valuesMissing
requirement1_9 has 440 (100.0%) missing valuesMissing
requirement1_10 has 440 (100.0%) missing valuesMissing
requirement2_1 has 340 (77.3%) missing valuesMissing
requirement2_2 has 395 (89.8%) missing valuesMissing
requirement2_3 has 405 (92.0%) missing valuesMissing
requirement2_4 has 411 (93.4%) missing valuesMissing
requirement2_5 has 423 (96.1%) missing valuesMissing
requirement2_6 has 431 (98.0%) missing valuesMissing
requirement2_7 has 434 (98.6%) missing valuesMissing
requirement2_8 has 439 (99.8%) missing valuesMissing
requirement2_9 has 440 (100.0%) missing valuesMissing
requirement2_10 has 440 (100.0%) missing valuesMissing
requirement3_1 has 347 (78.9%) missing valuesMissing
requirement3_2 has 397 (90.2%) missing valuesMissing
requirement3_3 has 406 (92.3%) missing valuesMissing
requirement3_4 has 413 (93.9%) missing valuesMissing
requirement3_5 has 424 (96.4%) missing valuesMissing
requirement3_6 has 432 (98.2%) missing valuesMissing
requirement3_7 has 434 (98.6%) missing valuesMissing
requirement3_8 has 439 (99.8%) missing valuesMissing
requirement3_9 has 440 (100.0%) missing valuesMissing
requirement3_10 has 440 (100.0%) missing valuesMissing
requirement4_1 has 387 (88.0%) missing valuesMissing
requirement4_2 has 414 (94.1%) missing valuesMissing
requirement4_3 has 420 (95.5%) missing valuesMissing
requirement4_4 has 426 (96.8%) missing valuesMissing
requirement4_5 has 431 (98.0%) missing valuesMissing
requirement4_6 has 438 (99.5%) missing valuesMissing
requirement4_7 has 438 (99.5%) missing valuesMissing
requirement4_8 has 440 (100.0%) missing valuesMissing
requirement4_9 has 440 (100.0%) missing valuesMissing
requirement4_10 has 440 (100.0%) missing valuesMissing
requirement5_1 has 419 (95.2%) missing valuesMissing
requirement5_2 has 428 (97.3%) missing valuesMissing
requirement5_3 has 431 (98.0%) missing valuesMissing
requirement5_4 has 434 (98.6%) missing valuesMissing
requirement5_5 has 436 (99.1%) missing valuesMissing
requirement5_6 has 439 (99.8%) missing valuesMissing
requirement5_7 has 439 (99.8%) missing valuesMissing
requirement5_8 has 440 (100.0%) missing valuesMissing
requirement5_9 has 440 (100.0%) missing valuesMissing
requirement5_10 has 440 (100.0%) missing valuesMissing
requirement6_1 has 436 (99.1%) missing valuesMissing
requirement6_2 has 438 (99.5%) missing valuesMissing
requirement6_3 has 438 (99.5%) missing valuesMissing
requirement6_4 has 440 (100.0%) missing valuesMissing
requirement6_5 has 440 (100.0%) missing valuesMissing
requirement6_6 has 440 (100.0%) missing valuesMissing
requirement6_7 has 439 (99.8%) missing valuesMissing
requirement6_8 has 440 (100.0%) missing valuesMissing
requirement6_9 has 440 (100.0%) missing valuesMissing
requirement6_10 has 440 (100.0%) missing valuesMissing
requirement7_1 has 440 (100.0%) missing valuesMissing
requirement7_2 has 440 (100.0%) missing valuesMissing
requirement7_3 has 440 (100.0%) missing valuesMissing
requirement7_4 has 440 (100.0%) missing valuesMissing
requirement7_5 has 440 (100.0%) missing valuesMissing
requirement7_6 has 440 (100.0%) missing valuesMissing
requirement7_7 has 440 (100.0%) missing valuesMissing
requirement7_8 has 440 (100.0%) missing valuesMissing
requirement7_9 has 440 (100.0%) missing valuesMissing
requirement7_10 has 440 (100.0%) missing valuesMissing
requirement8_1 has 440 (100.0%) missing valuesMissing
requirement8_2 has 440 (100.0%) missing valuesMissing
requirement8_3 has 440 (100.0%) missing valuesMissing
requirement8_4 has 440 (100.0%) missing valuesMissing
requirement8_5 has 440 (100.0%) missing valuesMissing
requirement8_6 has 440 (100.0%) missing valuesMissing
requirement8_7 has 440 (100.0%) missing valuesMissing
requirement8_8 has 440 (100.0%) missing valuesMissing
requirement8_9 has 440 (100.0%) missing valuesMissing
requirement8_10 has 440 (100.0%) missing valuesMissing
requirement9_1 has 440 (100.0%) missing valuesMissing
requirement9_2 has 440 (100.0%) missing valuesMissing
requirement9_3 has 440 (100.0%) missing valuesMissing
requirement9_4 has 440 (100.0%) missing valuesMissing
requirement9_5 has 440 (100.0%) missing valuesMissing
requirement9_6 has 440 (100.0%) missing valuesMissing
requirement9_7 has 440 (100.0%) missing valuesMissing
requirement9_8 has 440 (100.0%) missing valuesMissing
requirement9_9 has 440 (100.0%) missing valuesMissing
requirement9_10 has 440 (100.0%) missing valuesMissing
requirement10_1 has 440 (100.0%) missing valuesMissing
requirement10_2 has 440 (100.0%) missing valuesMissing
requirement10_3 has 440 (100.0%) missing valuesMissing
requirement10_4 has 440 (100.0%) missing valuesMissing
requirement10_5 has 440 (100.0%) missing valuesMissing
requirement10_6 has 440 (100.0%) missing valuesMissing
requirement10_7 has 440 (100.0%) missing valuesMissing
requirement10_8 has 440 (100.0%) missing valuesMissing
requirement10_9 has 440 (100.0%) missing valuesMissing
requirement10_10 has 440 (100.0%) missing valuesMissing
requirement11_1 has 440 (100.0%) missing valuesMissing
requirement11_2 has 440 (100.0%) missing valuesMissing
requirement11_3 has 440 (100.0%) missing valuesMissing
requirement11_4 has 440 (100.0%) missing valuesMissing
requirement11_5 has 440 (100.0%) missing valuesMissing
requirement11_6 has 440 (100.0%) missing valuesMissing
requirement11_7 has 440 (100.0%) missing valuesMissing
requirement11_8 has 440 (100.0%) missing valuesMissing
requirement11_9 has 440 (100.0%) missing valuesMissing
requirement11_10 has 440 (100.0%) missing valuesMissing
requirement12_1 has 440 (100.0%) missing valuesMissing
requirement12_2 has 440 (100.0%) missing valuesMissing
requirement12_3 has 440 (100.0%) missing valuesMissing
requirement12_4 has 440 (100.0%) missing valuesMissing
requirement12_5 has 440 (100.0%) missing valuesMissing
requirement12_6 has 440 (100.0%) missing valuesMissing
requirement12_7 has 440 (100.0%) missing valuesMissing
requirement12_8 has 440 (100.0%) missing valuesMissing
requirement12_9 has 440 (100.0%) missing valuesMissing
requirement12_10 has 440 (100.0%) missing valuesMissing
offer_rate1 has 117 (26.6%) missing valuesMissing
offer_rate2 has 382 (86.8%) missing valuesMissing
offer_rate3 has 413 (93.9%) missing valuesMissing
offer_rate4 has 419 (95.2%) missing valuesMissing
offer_rate5 has 427 (97.0%) missing valuesMissing
offer_rate6 has 431 (98.0%) missing valuesMissing
offer_rate7 has 435 (98.9%) missing valuesMissing
offer_rate8 has 438 (99.5%) missing valuesMissing
offer_rate9 has 439 (99.8%) missing valuesMissing
offer_rate10 has 440 (100.0%) missing valuesMissing
program2 has 312 (70.9%) missing valuesMissing
program3 has 370 (84.1%) missing valuesMissing
program4 has 387 (88.0%) missing valuesMissing
program5 has 402 (91.4%) missing valuesMissing
program6 has 416 (94.5%) missing valuesMissing
program7 has 426 (96.8%) missing valuesMissing
program8 has 433 (98.4%) missing valuesMissing
program9 has 438 (99.5%) missing valuesMissing
program10 has 439 (99.8%) missing valuesMissing
code2 has 312 (70.9%) missing valuesMissing
code3 has 370 (84.1%) missing valuesMissing
code4 has 387 (88.0%) missing valuesMissing
code5 has 402 (91.4%) missing valuesMissing
code6 has 416 (94.5%) missing valuesMissing
code7 has 426 (96.8%) missing valuesMissing
code8 has 433 (98.4%) missing valuesMissing
code9 has 438 (99.5%) missing valuesMissing
code10 has 439 (99.8%) missing valuesMissing
interest2 has 312 (70.9%) missing valuesMissing
interest3 has 370 (84.1%) missing valuesMissing
interest4 has 387 (88.0%) missing valuesMissing
interest5 has 402 (91.4%) missing valuesMissing
interest6 has 416 (94.5%) missing valuesMissing
interest7 has 426 (96.8%) missing valuesMissing
interest8 has 433 (98.4%) missing valuesMissing
interest9 has 438 (99.5%) missing valuesMissing
interest10 has 439 (99.8%) missing valuesMissing
method2 has 312 (70.9%) missing valuesMissing
method3 has 370 (84.1%) missing valuesMissing
method4 has 387 (88.0%) missing valuesMissing
method5 has 402 (91.4%) missing valuesMissing
method6 has 416 (94.5%) missing valuesMissing
method7 has 426 (96.8%) missing valuesMissing
method8 has 433 (98.4%) missing valuesMissing
method9 has 438 (99.5%) missing valuesMissing
method10 has 439 (99.8%) missing valuesMissing
seats9ge1 has 20 (4.5%) missing valuesMissing
seats9ge2 has 328 (74.5%) missing valuesMissing
seats9ge3 has 377 (85.7%) missing valuesMissing
seats9ge4 has 394 (89.5%) missing valuesMissing
seats9ge5 has 409 (93.0%) missing valuesMissing
seats9ge6 has 422 (95.9%) missing valuesMissing
seats9ge7 has 429 (97.5%) missing valuesMissing
seats9ge8 has 438 (99.5%) missing valuesMissing
seats9ge9 has 439 (99.8%) missing valuesMissing
seats9ge10 has 440 (100.0%) missing valuesMissing
grade9gefilledflag1 has 23 (5.2%) missing valuesMissing
grade9gefilledflag2 has 328 (74.5%) missing valuesMissing
grade9gefilledflag3 has 377 (85.7%) missing valuesMissing
grade9gefilledflag4 has 394 (89.5%) missing valuesMissing
grade9gefilledflag5 has 409 (93.0%) missing valuesMissing
grade9gefilledflag6 has 422 (95.9%) missing valuesMissing
grade9gefilledflag7 has 429 (97.5%) missing valuesMissing
grade9gefilledflag8 has 438 (99.5%) missing valuesMissing
grade9gefilledflag9 has 439 (99.8%) missing valuesMissing
grade9gefilledflag10 has 440 (100.0%) missing valuesMissing
grade9geapplicants1 has 20 (4.5%) missing valuesMissing
grade9geapplicants2 has 328 (74.5%) missing valuesMissing
grade9geapplicants3 has 377 (85.7%) missing valuesMissing
grade9geapplicants4 has 394 (89.5%) missing valuesMissing
grade9geapplicants5 has 409 (93.0%) missing valuesMissing
grade9geapplicants6 has 422 (95.9%) missing valuesMissing
grade9geapplicants7 has 429 (97.5%) missing valuesMissing
grade9geapplicants8 has 438 (99.5%) missing valuesMissing
grade9geapplicants9 has 439 (99.8%) missing valuesMissing
grade9geapplicants10 has 440 (100.0%) missing valuesMissing
seats9swd1 has 20 (4.5%) missing valuesMissing
seats9swd2 has 327 (74.3%) missing valuesMissing
seats9swd3 has 377 (85.7%) missing valuesMissing
seats9swd4 has 394 (89.5%) missing valuesMissing
seats9swd5 has 409 (93.0%) missing valuesMissing
seats9swd6 has 422 (95.9%) missing valuesMissing
seats9swd7 has 429 (97.5%) missing valuesMissing
seats9swd8 has 438 (99.5%) missing valuesMissing
seats9swd9 has 439 (99.8%) missing valuesMissing
seats9swd10 has 440 (100.0%) missing valuesMissing
grade9swdfilledflag1 has 23 (5.2%) missing valuesMissing
grade9swdfilledflag2 has 328 (74.5%) missing valuesMissing
grade9swdfilledflag3 has 377 (85.7%) missing valuesMissing
grade9swdfilledflag4 has 394 (89.5%) missing valuesMissing
grade9swdfilledflag5 has 409 (93.0%) missing valuesMissing
grade9swdfilledflag6 has 422 (95.9%) missing valuesMissing
grade9swdfilledflag7 has 429 (97.5%) missing valuesMissing
grade9swdfilledflag8 has 438 (99.5%) missing valuesMissing
grade9swdfilledflag9 has 439 (99.8%) missing valuesMissing
grade9swdfilledflag10 has 440 (100.0%) missing valuesMissing
grade9swdapplicants1 has 20 (4.5%) missing valuesMissing
grade9swdapplicants2 has 328 (74.5%) missing valuesMissing
grade9swdapplicants3 has 377 (85.7%) missing valuesMissing
grade9swdapplicants4 has 394 (89.5%) missing valuesMissing
grade9swdapplicants5 has 409 (93.0%) missing valuesMissing
grade9swdapplicants6 has 422 (95.9%) missing valuesMissing
grade9swdapplicants7 has 429 (97.5%) missing valuesMissing
grade9swdapplicants8 has 438 (99.5%) missing valuesMissing
grade9swdapplicants9 has 439 (99.8%) missing valuesMissing
grade9swdapplicants10 has 440 (100.0%) missing valuesMissing
seats1specialized has 431 (98.0%) missing valuesMissing
seats2specialized has 439 (99.8%) missing valuesMissing
seats3specialized has 439 (99.8%) missing valuesMissing
seats4specialized has 439 (99.8%) missing valuesMissing
seats5specialized has 439 (99.8%) missing valuesMissing
seats6specialized has 439 (99.8%) missing valuesMissing
applicants1specialized has 431 (98.0%) missing valuesMissing
applicants2specialized has 439 (99.8%) missing valuesMissing
applicants3specialized has 439 (99.8%) missing valuesMissing
applicants4specialized has 439 (99.8%) missing valuesMissing
applicants5specialized has 439 (99.8%) missing valuesMissing
applicants6specialized has 439 (99.8%) missing valuesMissing
appperseat1specialized has 431 (98.0%) missing valuesMissing
appperseat2specialized has 439 (99.8%) missing valuesMissing
appperseat3specialized has 439 (99.8%) missing valuesMissing
appperseat4specialized has 439 (99.8%) missing valuesMissing
appperseat5specialized has 439 (99.8%) missing valuesMissing
appperseat6specialized has 439 (99.8%) missing valuesMissing
seats102 has 312 (70.9%) missing valuesMissing
seats103 has 370 (84.1%) missing valuesMissing
seats104 has 387 (88.0%) missing valuesMissing
seats105 has 402 (91.4%) missing valuesMissing
seats106 has 416 (94.5%) missing valuesMissing
seats107 has 426 (96.8%) missing valuesMissing
seats108 has 433 (98.4%) missing valuesMissing
seats109 has 438 (99.5%) missing valuesMissing
seats1010 has 439 (99.8%) missing valuesMissing
admissionspriority11 has 42 (9.5%) missing valuesMissing
admissionspriority12 has 335 (76.1%) missing valuesMissing
admissionspriority13 has 379 (86.1%) missing valuesMissing
admissionspriority14 has 394 (89.5%) missing valuesMissing
admissionspriority15 has 406 (92.3%) missing valuesMissing
admissionspriority16 has 418 (95.0%) missing valuesMissing
admissionspriority17 has 427 (97.0%) missing valuesMissing
admissionspriority18 has 433 (98.4%) missing valuesMissing
admissionspriority19 has 438 (99.5%) missing valuesMissing
admissionspriority110 has 439 (99.8%) missing valuesMissing
admissionspriority21 has 114 (25.9%) missing valuesMissing
admissionspriority22 has 379 (86.1%) missing valuesMissing
admissionspriority23 has 412 (93.6%) missing valuesMissing
admissionspriority24 has 419 (95.2%) missing valuesMissing
admissionspriority25 has 425 (96.6%) missing valuesMissing
admissionspriority26 has 431 (98.0%) missing valuesMissing
admissionspriority27 has 434 (98.6%) missing valuesMissing
admissionspriority28 has 437 (99.3%) missing valuesMissing
admissionspriority29 has 439 (99.8%) missing valuesMissing
admissionspriority210 has 440 (100.0%) missing valuesMissing
admissionspriority31 has 234 (53.2%) missing valuesMissing
admissionspriority32 has 414 (94.1%) missing valuesMissing
admissionspriority33 has 434 (98.6%) missing valuesMissing
admissionspriority34 has 433 (98.4%) missing valuesMissing
admissionspriority35 has 435 (98.9%) missing valuesMissing
admissionspriority36 has 439 (99.8%) missing valuesMissing
admissionspriority37 has 439 (99.8%) missing valuesMissing
admissionspriority38 has 440 (100.0%) missing valuesMissing
admissionspriority39 has 440 (100.0%) missing valuesMissing
admissionspriority310 has 440 (100.0%) missing valuesMissing
admissionspriority41 has 284 (64.5%) missing valuesMissing
admissionspriority42 has 423 (96.1%) missing valuesMissing
admissionspriority43 has 438 (99.5%) missing valuesMissing
admissionspriority44 has 437 (99.3%) missing valuesMissing
admissionspriority45 has 440 (100.0%) missing valuesMissing
admissionspriority46 has 439 (99.8%) missing valuesMissing
admissionspriority47 has 440 (100.0%) missing valuesMissing
admissionspriority48 has 440 (100.0%) missing valuesMissing
admissionspriority49 has 440 (100.0%) missing valuesMissing
admissionspriority410 has 440 (100.0%) missing valuesMissing
admissionspriority51 has 407 (92.5%) missing valuesMissing
admissionspriority52 has 437 (99.3%) missing valuesMissing
admissionspriority53 has 439 (99.8%) missing valuesMissing
admissionspriority54 has 439 (99.8%) missing valuesMissing
admissionspriority55 has 440 (100.0%) missing valuesMissing
admissionspriority56 has 439 (99.8%) missing valuesMissing
admissionspriority57 has 440 (100.0%) missing valuesMissing
admissionspriority58 has 440 (100.0%) missing valuesMissing
admissionspriority59 has 440 (100.0%) missing valuesMissing
admissionspriority510 has 440 (100.0%) missing valuesMissing
admissionspriority61 has 428 (97.3%) missing valuesMissing
admissionspriority62 has 439 (99.8%) missing valuesMissing
admissionspriority63 has 439 (99.8%) missing valuesMissing
admissionspriority64 has 439 (99.8%) missing valuesMissing
admissionspriority65 has 440 (100.0%) missing valuesMissing
admissionspriority66 has 440 (100.0%) missing valuesMissing
admissionspriority67 has 440 (100.0%) missing valuesMissing
admissionspriority68 has 440 (100.0%) missing valuesMissing
admissionspriority69 has 440 (100.0%) missing valuesMissing
admissionspriority610 has 440 (100.0%) missing valuesMissing
admissionspriority71 has 438 (99.5%) missing valuesMissing
admissionspriority72 has 440 (100.0%) missing valuesMissing
admissionspriority73 has 440 (100.0%) missing valuesMissing
admissionspriority74 has 439 (99.8%) missing valuesMissing
admissionspriority75 has 440 (100.0%) missing valuesMissing
admissionspriority76 has 440 (100.0%) missing valuesMissing
admissionspriority77 has 440 (100.0%) missing valuesMissing
admissionspriority78 has 440 (100.0%) missing valuesMissing
admissionspriority79 has 440 (100.0%) missing valuesMissing
admissionspriority710 has 440 (100.0%) missing valuesMissing
eligibility1 has 375 (85.2%) missing valuesMissing
eligibility2 has 412 (93.6%) missing valuesMissing
eligibility3 has 430 (97.7%) missing valuesMissing
eligibility4 has 433 (98.4%) missing valuesMissing
eligibility5 has 436 (99.1%) missing valuesMissing
eligibility6 has 438 (99.5%) missing valuesMissing
eligibility7 has 439 (99.8%) missing valuesMissing
eligibility8 has 440 (100.0%) missing valuesMissing
eligibility9 has 440 (100.0%) missing valuesMissing
eligibility10 has 440 (100.0%) missing valuesMissing
auditioninformation1 has 422 (95.9%) missing valuesMissing
auditioninformation2 has 424 (96.4%) missing valuesMissing
auditioninformation3 has 426 (96.8%) missing valuesMissing
auditioninformation4 has 427 (97.0%) missing valuesMissing
auditioninformation5 has 428 (97.3%) missing valuesMissing
auditioninformation6 has 436 (99.1%) missing valuesMissing
auditioninformation7 has 438 (99.5%) missing valuesMissing
auditioninformation8 has 440 (100.0%) missing valuesMissing
auditioninformation9 has 440 (100.0%) missing valuesMissing
auditioninformation10 has 440 (100.0%) missing valuesMissing
common_audition1 has 430 (97.7%) missing valuesMissing
common_audition2 has 430 (97.7%) missing valuesMissing
common_audition3 has 432 (98.2%) missing valuesMissing
common_audition4 has 434 (98.6%) missing valuesMissing
common_audition5 has 432 (98.2%) missing valuesMissing
common_audition6 has 438 (99.5%) missing valuesMissing
common_audition7 has 439 (99.8%) missing valuesMissing
common_audition8 has 440 (100.0%) missing valuesMissing
common_audition9 has 440 (100.0%) missing valuesMissing
common_audition10 has 440 (100.0%) missing valuesMissing
grade9geapplicantsperseat1 has 20 (4.5%) missing valuesMissing
grade9geapplicantsperseat2 has 328 (74.5%) missing valuesMissing
grade9geapplicantsperseat3 has 377 (85.7%) missing valuesMissing
grade9geapplicantsperseat4 has 394 (89.5%) missing valuesMissing
grade9geapplicantsperseat5 has 409 (93.0%) missing valuesMissing
grade9geapplicantsperseat6 has 422 (95.9%) missing valuesMissing
grade9geapplicantsperseat7 has 429 (97.5%) missing valuesMissing
grade9geapplicantsperseat8 has 438 (99.5%) missing valuesMissing
grade9geapplicantsperseat9 has 439 (99.8%) missing valuesMissing
grade9geapplicantsperseat10 has 440 (100.0%) missing valuesMissing
grade9swdapplicantsperseat1 has 20 (4.5%) missing valuesMissing
grade9swdapplicantsperseat2 has 329 (74.8%) missing valuesMissing
grade9swdapplicantsperseat3 has 379 (86.1%) missing valuesMissing
grade9swdapplicantsperseat4 has 395 (89.8%) missing valuesMissing
grade9swdapplicantsperseat5 has 409 (93.0%) missing valuesMissing
grade9swdapplicantsperseat6 has 422 (95.9%) missing valuesMissing
grade9swdapplicantsperseat7 has 429 (97.5%) missing valuesMissing
grade9swdapplicantsperseat8 has 438 (99.5%) missing valuesMissing
grade9swdapplicantsperseat9 has 439 (99.8%) missing valuesMissing
grade9swdapplicantsperseat10 has 440 (100.0%) missing valuesMissing
0 has unique valuesUnique
dbn has unique valuesUnique
school_name has unique valuesUnique
overview_paragraph has unique valuesUnique
directions8 is an unsupported type, check if it needs cleaning or further analysisUnsupported
directions9 is an unsupported type, check if it needs cleaning or further analysisUnsupported
directions10 is an unsupported type, check if it needs cleaning or further analysisUnsupported
requirement1_9 is an unsupported type, check if it needs cleaning or further analysisUnsupported
requirement1_10 is an unsupported type, check if it needs cleaning or further analysisUnsupported
requirement2_9 is an unsupported type, check if it needs cleaning or further analysisUnsupported
requirement2_10 is an unsupported type, check if it needs cleaning or further analysisUnsupported
requirement3_9 is an unsupported type, check if it needs cleaning or further analysisUnsupported
requirement3_10 is an unsupported type, check if it needs cleaning or further analysisUnsupported
requirement4_8 is an unsupported type, check if it needs cleaning or further analysisUnsupported
requirement4_9 is an unsupported type, check if it needs cleaning or further analysisUnsupported
requirement4_10 is an unsupported type, check if it needs cleaning or further analysisUnsupported
requirement5_8 is an unsupported type, check if it needs cleaning or further analysisUnsupported
requirement5_9 is an unsupported type, check if it needs cleaning or further analysisUnsupported
requirement5_10 is an unsupported type, check if it needs cleaning or further analysisUnsupported
requirement6_4 is an unsupported type, check if it needs cleaning or further analysisUnsupported
requirement6_5 is an unsupported type, check if it needs cleaning or further analysisUnsupported
requirement6_6 is an unsupported type, check if it needs cleaning or further analysisUnsupported
requirement6_8 is an unsupported type, check if it needs cleaning or further analysisUnsupported
requirement6_9 is an unsupported type, check if it needs cleaning or further analysisUnsupported
requirement6_10 is an unsupported type, check if it needs cleaning or further analysisUnsupported
requirement7_1 is an unsupported type, check if it needs cleaning or further analysisUnsupported
requirement7_2 is an unsupported type, check if it needs cleaning or further analysisUnsupported
requirement7_3 is an unsupported type, check if it needs cleaning or further analysisUnsupported
requirement7_4 is an unsupported type, check if it needs cleaning or further analysisUnsupported
requirement7_5 is an unsupported type, check if it needs cleaning or further analysisUnsupported
requirement7_6 is an unsupported type, check if it needs cleaning or further analysisUnsupported
requirement7_7 is an unsupported type, check if it needs cleaning or further analysisUnsupported
requirement7_8 is an unsupported type, check if it needs cleaning or further analysisUnsupported
requirement7_9 is an unsupported type, check if it needs cleaning or further analysisUnsupported
requirement7_10 is an unsupported type, check if it needs cleaning or further analysisUnsupported
requirement8_1 is an unsupported type, check if it needs cleaning or further analysisUnsupported
requirement8_2 is an unsupported type, check if it needs cleaning or further analysisUnsupported
requirement8_3 is an unsupported type, check if it needs cleaning or further analysisUnsupported
requirement8_4 is an unsupported type, check if it needs cleaning or further analysisUnsupported
requirement8_5 is an unsupported type, check if it needs cleaning or further analysisUnsupported
requirement8_6 is an unsupported type, check if it needs cleaning or further analysisUnsupported
requirement8_7 is an unsupported type, check if it needs cleaning or further analysisUnsupported
requirement8_8 is an unsupported type, check if it needs cleaning or further analysisUnsupported
requirement8_9 is an unsupported type, check if it needs cleaning or further analysisUnsupported
requirement8_10 is an unsupported type, check if it needs cleaning or further analysisUnsupported
requirement9_1 is an unsupported type, check if it needs cleaning or further analysisUnsupported
requirement9_2 is an unsupported type, check if it needs cleaning or further analysisUnsupported
requirement9_3 is an unsupported type, check if it needs cleaning or further analysisUnsupported
requirement9_4 is an unsupported type, check if it needs cleaning or further analysisUnsupported
requirement9_5 is an unsupported type, check if it needs cleaning or further analysisUnsupported
requirement9_6 is an unsupported type, check if it needs cleaning or further analysisUnsupported
requirement9_7 is an unsupported type, check if it needs cleaning or further analysisUnsupported
requirement9_8 is an unsupported type, check if it needs cleaning or further analysisUnsupported
requirement9_9 is an unsupported type, check if it needs cleaning or further analysisUnsupported
requirement9_10 is an unsupported type, check if it needs cleaning or further analysisUnsupported
requirement10_1 is an unsupported type, check if it needs cleaning or further analysisUnsupported
requirement10_2 is an unsupported type, check if it needs cleaning or further analysisUnsupported
requirement10_3 is an unsupported type, check if it needs cleaning or further analysisUnsupported
requirement10_4 is an unsupported type, check if it needs cleaning or further analysisUnsupported
requirement10_5 is an unsupported type, check if it needs cleaning or further analysisUnsupported
requirement10_6 is an unsupported type, check if it needs cleaning or further analysisUnsupported
requirement10_7 is an unsupported type, check if it needs cleaning or further analysisUnsupported
requirement10_8 is an unsupported type, check if it needs cleaning or further analysisUnsupported
requirement10_9 is an unsupported type, check if it needs cleaning or further analysisUnsupported
requirement10_10 is an unsupported type, check if it needs cleaning or further analysisUnsupported
requirement11_1 is an unsupported type, check if it needs cleaning or further analysisUnsupported
requirement11_2 is an unsupported type, check if it needs cleaning or further analysisUnsupported
requirement11_3 is an unsupported type, check if it needs cleaning or further analysisUnsupported
requirement11_4 is an unsupported type, check if it needs cleaning or further analysisUnsupported
requirement11_5 is an unsupported type, check if it needs cleaning or further analysisUnsupported
requirement11_6 is an unsupported type, check if it needs cleaning or further analysisUnsupported
requirement11_7 is an unsupported type, check if it needs cleaning or further analysisUnsupported
requirement11_8 is an unsupported type, check if it needs cleaning or further analysisUnsupported
requirement11_9 is an unsupported type, check if it needs cleaning or further analysisUnsupported
requirement11_10 is an unsupported type, check if it needs cleaning or further analysisUnsupported
requirement12_1 is an unsupported type, check if it needs cleaning or further analysisUnsupported
requirement12_2 is an unsupported type, check if it needs cleaning or further analysisUnsupported
requirement12_3 is an unsupported type, check if it needs cleaning or further analysisUnsupported
requirement12_4 is an unsupported type, check if it needs cleaning or further analysisUnsupported
requirement12_5 is an unsupported type, check if it needs cleaning or further analysisUnsupported
requirement12_6 is an unsupported type, check if it needs cleaning or further analysisUnsupported
requirement12_7 is an unsupported type, check if it needs cleaning or further analysisUnsupported
requirement12_8 is an unsupported type, check if it needs cleaning or further analysisUnsupported
requirement12_9 is an unsupported type, check if it needs cleaning or further analysisUnsupported
requirement12_10 is an unsupported type, check if it needs cleaning or further analysisUnsupported
offer_rate10 is an unsupported type, check if it needs cleaning or further analysisUnsupported
seats9ge10 is an unsupported type, check if it needs cleaning or further analysisUnsupported
grade9gefilledflag10 is an unsupported type, check if it needs cleaning or further analysisUnsupported
grade9geapplicants10 is an unsupported type, check if it needs cleaning or further analysisUnsupported
seats9swd10 is an unsupported type, check if it needs cleaning or further analysisUnsupported
grade9swdfilledflag10 is an unsupported type, check if it needs cleaning or further analysisUnsupported
grade9swdapplicants10 is an unsupported type, check if it needs cleaning or further analysisUnsupported
admissionspriority210 is an unsupported type, check if it needs cleaning or further analysisUnsupported
admissionspriority38 is an unsupported type, check if it needs cleaning or further analysisUnsupported
admissionspriority39 is an unsupported type, check if it needs cleaning or further analysisUnsupported
admissionspriority310 is an unsupported type, check if it needs cleaning or further analysisUnsupported
admissionspriority45 is an unsupported type, check if it needs cleaning or further analysisUnsupported
admissionspriority47 is an unsupported type, check if it needs cleaning or further analysisUnsupported
admissionspriority48 is an unsupported type, check if it needs cleaning or further analysisUnsupported
admissionspriority49 is an unsupported type, check if it needs cleaning or further analysisUnsupported
admissionspriority410 is an unsupported type, check if it needs cleaning or further analysisUnsupported
admissionspriority55 is an unsupported type, check if it needs cleaning or further analysisUnsupported
admissionspriority57 is an unsupported type, check if it needs cleaning or further analysisUnsupported
admissionspriority58 is an unsupported type, check if it needs cleaning or further analysisUnsupported
admissionspriority59 is an unsupported type, check if it needs cleaning or further analysisUnsupported
admissionspriority510 is an unsupported type, check if it needs cleaning or further analysisUnsupported
admissionspriority65 is an unsupported type, check if it needs cleaning or further analysisUnsupported
admissionspriority66 is an unsupported type, check if it needs cleaning or further analysisUnsupported
admissionspriority67 is an unsupported type, check if it needs cleaning or further analysisUnsupported
admissionspriority68 is an unsupported type, check if it needs cleaning or further analysisUnsupported
admissionspriority69 is an unsupported type, check if it needs cleaning or further analysisUnsupported
admissionspriority610 is an unsupported type, check if it needs cleaning or further analysisUnsupported
admissionspriority72 is an unsupported type, check if it needs cleaning or further analysisUnsupported
admissionspriority73 is an unsupported type, check if it needs cleaning or further analysisUnsupported
admissionspriority75 is an unsupported type, check if it needs cleaning or further analysisUnsupported
admissionspriority76 is an unsupported type, check if it needs cleaning or further analysisUnsupported
admissionspriority77 is an unsupported type, check if it needs cleaning or further analysisUnsupported
admissionspriority78 is an unsupported type, check if it needs cleaning or further analysisUnsupported
admissionspriority79 is an unsupported type, check if it needs cleaning or further analysisUnsupported
admissionspriority710 is an unsupported type, check if it needs cleaning or further analysisUnsupported
eligibility8 is an unsupported type, check if it needs cleaning or further analysisUnsupported
eligibility9 is an unsupported type, check if it needs cleaning or further analysisUnsupported
eligibility10 is an unsupported type, check if it needs cleaning or further analysisUnsupported
auditioninformation8 is an unsupported type, check if it needs cleaning or further analysisUnsupported
auditioninformation9 is an unsupported type, check if it needs cleaning or further analysisUnsupported
auditioninformation10 is an unsupported type, check if it needs cleaning or further analysisUnsupported
common_audition8 is an unsupported type, check if it needs cleaning or further analysisUnsupported
common_audition9 is an unsupported type, check if it needs cleaning or further analysisUnsupported
common_audition10 is an unsupported type, check if it needs cleaning or further analysisUnsupported
grade9geapplicantsperseat10 is an unsupported type, check if it needs cleaning or further analysisUnsupported
grade9swdapplicantsperseat10 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-12-09 22:06:15.593573
Analysis finished2023-12-09 22:06:29.631917
Duration14.04 seconds
Software versionydata-profiling v0.0.dev0
Download configurationconfig.json

Variables

0
Real number (ℝ)

UNIQUE 

Distinct440
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean220.5
Minimum1
Maximum440
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.6 KiB
2023-12-09T22:06:30.126771image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile22.95
Q1110.75
median220.5
Q3330.25
95-th percentile418.05
Maximum440
Range439
Interquartile range (IQR)219.5

Descriptive statistics

Standard deviation127.1613149
Coefficient of variation (CV)0.5766953055
Kurtosis-1.2
Mean220.5
Median Absolute Deviation (MAD)110
Skewness0
Sum97020
Variance16170
MonotonicityStrictly increasing
2023-12-09T22:06:30.306111image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.2%
290 1
 
0.2%
301 1
 
0.2%
300 1
 
0.2%
299 1
 
0.2%
298 1
 
0.2%
297 1
 
0.2%
296 1
 
0.2%
295 1
 
0.2%
294 1
 
0.2%
Other values (430) 430
97.7%
ValueCountFrequency (%)
1 1
0.2%
2 1
0.2%
3 1
0.2%
4 1
0.2%
5 1
0.2%
ValueCountFrequency (%)
440 1
0.2%
439 1
0.2%
438 1
0.2%
437 1
0.2%
436 1
0.2%

dbn
Text

UNIQUE 

Distinct440
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size27.2 KiB
2023-12-09T22:06:31.035886image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters2640
Distinct characters15
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique440 ?
Unique (%)100.0%

Sample

1st row02M260
2nd row21K728
3rd row08X282
4th row17K548
5th row27Q314
ValueCountFrequency (%)
17k546 1
 
0.2%
19k660 1
 
0.2%
13k483 1
 
0.2%
20k445 1
 
0.2%
14k454 1
 
0.2%
09x505 1
 
0.2%
28q325 1
 
0.2%
19k404 1
 
0.2%
04m680 1
 
0.2%
02m519 1
 
0.2%
Other values (430) 430
97.7%
2023-12-09T22:06:31.602515image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 349
13.2%
0 331
12.5%
1 271
10.3%
4 254
9.6%
5 248
9.4%
3 202
7.7%
6 155
 
5.9%
9 141
 
5.3%
8 127
 
4.8%
K 124
 
4.7%
Other values (5) 438
16.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2200
83.3%
Uppercase Letter 440
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 349
15.9%
0 331
15.0%
1 271
12.3%
4 254
11.5%
5 248
11.3%
3 202
9.2%
6 155
7.0%
9 141
6.4%
8 127
 
5.8%
7 122
 
5.5%
Uppercase Letter
ValueCountFrequency (%)
K 124
28.2%
X 118
26.8%
M 108
24.5%
Q 80
18.2%
R 10
 
2.3%

Most occurring scripts

ValueCountFrequency (%)
Common 2200
83.3%
Latin 440
 
16.7%

Most frequent character per script

Common
ValueCountFrequency (%)
2 349
15.9%
0 331
15.0%
1 271
12.3%
4 254
11.5%
5 248
11.3%
3 202
9.2%
6 155
7.0%
9 141
6.4%
8 127
 
5.8%
7 122
 
5.5%
Latin
ValueCountFrequency (%)
K 124
28.2%
X 118
26.8%
M 108
24.5%
Q 80
18.2%
R 10
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2640
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 349
13.2%
0 331
12.5%
1 271
10.3%
4 254
9.6%
5 248
9.4%
3 202
7.7%
6 155
 
5.9%
9 141
 
5.3%
8 127
 
4.8%
K 124
 
4.7%
Other values (5) 438
16.6%

school_name
Text

UNIQUE 

Distinct440
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size41.0 KiB
2023-12-09T22:06:31.961312image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length83
Median length59
Mean length37.55909091
Min length11

Characters and Unicode

Total characters16526
Distinct characters74
Distinct categories11 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique440 ?
Unique (%)100.0%

Sample

1st rowClinton School Writers & Artists, M.S. 260
2nd rowLiberation Diploma Plus High School
3rd rowWomen's Academy of Excellence
4th rowBrooklyn School for Music & Theatre
5th rowEpic High School - South
ValueCountFrequency (%)
school 349
 
14.3%
high 239
 
9.8%
for 136
 
5.6%
academy 101
 
4.1%
and 96
 
3.9%
the 59
 
2.4%
of 56
 
2.3%
bronx 38
 
1.6%
arts 37
 
1.5%
college 36
 
1.5%
Other values (537) 1301
53.1%
2023-12-09T22:06:32.506523image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2008
 
12.2%
o 1553
 
9.4%
e 1146
 
6.9%
a 950
 
5.7%
n 867
 
5.2%
i 857
 
5.2%
r 852
 
5.2%
h 846
 
5.1%
l 839
 
5.1%
c 780
 
4.7%
Other values (64) 5828
35.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 12076
73.1%
Uppercase Letter 2237
 
13.5%
Space Separator 2008
 
12.2%
Other Punctuation 112
 
0.7%
Open Punctuation 32
 
0.2%
Close Punctuation 32
 
0.2%
Decimal Number 17
 
0.1%
Dash Punctuation 8
 
< 0.1%
Final Punctuation 2
 
< 0.1%
Initial Punctuation 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 1553
12.9%
e 1146
9.5%
a 950
 
7.9%
n 867
 
7.2%
i 857
 
7.1%
r 852
 
7.1%
h 846
 
7.0%
l 839
 
6.9%
c 780
 
6.5%
t 568
 
4.7%
Other values (16) 2818
23.3%
Uppercase Letter
ValueCountFrequency (%)
S 490
21.9%
H 309
13.8%
A 228
10.2%
C 177
 
7.9%
T 124
 
5.5%
B 117
 
5.2%
E 98
 
4.4%
M 98
 
4.4%
L 89
 
4.0%
P 84
 
3.8%
Other values (15) 423
18.9%
Decimal Number
ValueCountFrequency (%)
2 4
23.5%
3 3
17.6%
7 2
11.8%
6 2
11.8%
4 2
11.8%
1 2
11.8%
0 1
 
5.9%
8 1
 
5.9%
Other Punctuation
ValueCountFrequency (%)
, 37
33.0%
. 35
31.2%
& 15
13.4%
: 15
13.4%
' 6
 
5.4%
/ 4
 
3.6%
Dash Punctuation
ValueCountFrequency (%)
- 7
87.5%
– 1
 
12.5%
Final Punctuation
ValueCountFrequency (%)
’ 1
50.0%
” 1
50.0%
Space Separator
ValueCountFrequency (%)
2008
100.0%
Open Punctuation
ValueCountFrequency (%)
( 32
100.0%
Close Punctuation
ValueCountFrequency (%)
) 32
100.0%
Initial Punctuation
ValueCountFrequency (%)
“ 1
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 14313
86.6%
Common 2213
 
13.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 1553
 
10.9%
e 1146
 
8.0%
a 950
 
6.6%
n 867
 
6.1%
i 857
 
6.0%
r 852
 
6.0%
h 846
 
5.9%
l 839
 
5.9%
c 780
 
5.4%
t 568
 
4.0%
Other values (41) 5055
35.3%
Common
ValueCountFrequency (%)
2008
90.7%
, 37
 
1.7%
. 35
 
1.6%
( 32
 
1.4%
) 32
 
1.4%
& 15
 
0.7%
: 15
 
0.7%
- 7
 
0.3%
' 6
 
0.3%
/ 4
 
0.2%
Other values (13) 22
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 16518
> 99.9%
None 4
 
< 0.1%
Punctuation 4
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2008
 
12.2%
o 1553
 
9.4%
e 1146
 
6.9%
a 950
 
5.8%
n 867
 
5.2%
i 857
 
5.2%
r 852
 
5.2%
h 846
 
5.1%
l 839
 
5.1%
c 780
 
4.7%
Other values (59) 5820
35.2%
None
ValueCountFrequency (%)
 4
100.0%
Punctuation
ValueCountFrequency (%)
“ 1
25.0%
’ 1
25.0%
– 1
25.0%
” 1
25.0%

boro
Text

Distinct5
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size25.0 KiB
2023-12-09T22:06:32.650895image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters440
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowM
2nd rowK
3rd rowX
4th rowK
5th rowQ
ValueCountFrequency (%)
k 124
28.2%
x 118
26.8%
m 108
24.5%
q 80
18.2%
r 10
 
2.3%
2023-12-09T22:06:32.891036image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
K 124
28.2%
X 118
26.8%
M 108
24.5%
Q 80
18.2%
R 10
 
2.3%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 440
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
K 124
28.2%
X 118
26.8%
M 108
24.5%
Q 80
18.2%
R 10
 
2.3%

Most occurring scripts

ValueCountFrequency (%)
Latin 440
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
K 124
28.2%
X 118
26.8%
M 108
24.5%
Q 80
18.2%
R 10
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 440
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
K 124
28.2%
X 118
26.8%
M 108
24.5%
Q 80
18.2%
R 10
 
2.3%

overview_paragraph
Text

UNIQUE 

Distinct440
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size369.8 KiB
2023-12-09T22:06:33.263479image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1128
Median length678
Mean length605.7522727
Min length122

Characters and Unicode

Total characters266531
Distinct characters88
Distinct categories14 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique440 ?
Unique (%)100.0%

Sample

1st rowStudents who are prepared for college must have an education that encourages them to take risks as they produce and perform. Our college preparatory curriculum develops writers and has built a tight-knit community. Our school develops students who can think analytically and write creatively. Our arts programming builds on our 25 years of experience in visual, performing arts and music on a middle school level. We partner with New Audience and the Whitney Museum as cultural partners. We are a International Baccalaureate (IB) candidate school that offers opportunities to take college courses at neighboring universities.
2nd rowThe mission of Liberation Diploma Plus High School, in partnership with CAMBA, is to develop the student academically, socially, and emotionally. We will equip students with the skills needed to evaluate their options so that they can make informed and appropriate choices and create personal goals for success. Our year-round model (trimesters plus summer school) provides students the opportunity to gain credits and attain required graduation competencies at an accelerated rate. Our partners offer all students career preparation and college exposure. Students have the opportunity to earn college credit(s). In addition to fulfilling New York City graduation requirements, students are required to complete a portfolio to receive a high school diploma.
3rd rowThe WomenÂ’s Academy of Excellence is an all-girls public high school, serving grades 9-12. Our mission is to create a community of lifelong learners, to nurture the intellectual curiosity and creativity of young women and to address their developmental needs. The school community cultivates dynamic, participatory learning, enabling students to achieve academic success at many levels, especially in the fields of math, science, and civic responsibility. Our scholars are exposed to a challenging curriculum that encourages them to achieve their goals while being empowered to become young women and leaders. Our Philosophy is GIRLS MATTER!
4th rowBrooklyn School for Music & Theatre (BSMT) uses our academic program to accommodate the intellectual, social, and emotional needs of creative high school students. Our vision is to provide a model professional environment where respect is mutual, ideas are shared, and learning is not limited to the classroom. We prepare students for higher education through our rigorous academic program while simultaneously allowing them to develop professional careers in the music and theatre industries.
5th rowEpic High School – South, an outgrowth of the NYC Expanded Success Initiative (ESI), provides a rigorous, culturally relevant academic program that prepares students for the demands of college and careers. Epic’s personalized approach to instruction challenges students to dream big and design their futures. It engages students in solving real-world problems and supports their individual progress and growth. Epic students graduate with confidence in their ability to transform the world around them.
ValueCountFrequency (%)
and 2315
 
5.9%
to 1324
 
3.4%
the 1301
 
3.3%
students 1126
 
2.9%
a 975
 
2.5%
of 949
 
2.4%
in 922
 
2.4%
our 864
 
2.2%
school 649
 
1.7%
for 517
 
1.3%
Other values (3646) 28176
72.0%
2023-12-09T22:06:33.826992image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
38686
14.5%
e 25941
 
9.7%
t 17775
 
6.7%
a 16902
 
6.3%
n 16511
 
6.2%
o 15932
 
6.0%
i 15863
 
6.0%
r 15146
 
5.7%
s 15084
 
5.7%
l 10612
 
4.0%
Other values (78) 78079
29.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 214953
80.6%
Space Separator 38686
 
14.5%
Uppercase Letter 6619
 
2.5%
Other Punctuation 4648
 
1.7%
Dash Punctuation 724
 
0.3%
Decimal Number 350
 
0.1%
Close Punctuation 178
 
0.1%
Open Punctuation 175
 
0.1%
Final Punctuation 165
 
0.1%
Initial Punctuation 26
 
< 0.1%
Other values (4) 7
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
S 802
12.1%
C 644
 
9.7%
A 637
 
9.6%
T 486
 
7.3%
W 477
 
7.2%
O 440
 
6.6%
E 402
 
6.1%
H 271
 
4.1%
P 250
 
3.8%
B 247
 
3.7%
Other values (18) 1963
29.7%
Lowercase Letter
ValueCountFrequency (%)
e 25941
12.1%
t 17775
 
8.3%
a 16902
 
7.9%
n 16511
 
7.7%
o 15932
 
7.4%
i 15863
 
7.4%
r 15146
 
7.0%
s 15084
 
7.0%
l 10612
 
4.9%
c 9832
 
4.6%
Other values (16) 55355
25.8%
Other Punctuation
ValueCountFrequency (%)
, 2534
54.5%
. 1950
42.0%
/ 42
 
0.9%
: 37
 
0.8%
' 29
 
0.6%
; 17
 
0.4%
& 15
 
0.3%
! 10
 
0.2%
? 7
 
0.2%
% 7
 
0.2%
Decimal Number
ValueCountFrequency (%)
1 112
32.0%
2 77
22.0%
0 65
18.6%
9 28
 
8.0%
4 19
 
5.4%
6 15
 
4.3%
5 14
 
4.0%
3 9
 
2.6%
8 8
 
2.3%
7 3
 
0.9%
Dash Punctuation
ValueCountFrequency (%)
- 687
94.9%
– 25
 
3.5%
— 12
 
1.7%
Final Punctuation
ValueCountFrequency (%)
’ 149
90.3%
” 16
 
9.7%
Initial Punctuation
ValueCountFrequency (%)
“ 16
61.5%
‘ 10
38.5%
Space Separator
ValueCountFrequency (%)
38686
100.0%
Close Punctuation
ValueCountFrequency (%)
) 178
100.0%
Open Punctuation
ValueCountFrequency (%)
( 175
100.0%
Math Symbol
ValueCountFrequency (%)
+ 3
100.0%
Other Symbol
ValueCountFrequency (%)
© 2
100.0%
Currency Symbol
ValueCountFrequency (%)
$ 1
100.0%
Other Number
ValueCountFrequency (%)
³ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 221572
83.1%
Common 44959
 
16.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 25941
11.7%
t 17775
 
8.0%
a 16902
 
7.6%
n 16511
 
7.5%
o 15932
 
7.2%
i 15863
 
7.2%
r 15146
 
6.8%
s 15084
 
6.8%
l 10612
 
4.8%
c 9832
 
4.4%
Other values (44) 61974
28.0%
Common
ValueCountFrequency (%)
38686
86.0%
, 2534
 
5.6%
. 1950
 
4.3%
- 687
 
1.5%
) 178
 
0.4%
( 175
 
0.4%
’ 149
 
0.3%
1 112
 
0.2%
2 77
 
0.2%
0 65
 
0.1%
Other values (24) 346
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 266069
99.8%
None 234
 
0.1%
Punctuation 228
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
38686
14.5%
e 25941
 
9.7%
t 17775
 
6.7%
a 16902
 
6.4%
n 16511
 
6.2%
o 15932
 
6.0%
i 15863
 
6.0%
r 15146
 
5.7%
s 15084
 
5.7%
l 10612
 
4.0%
Other values (68) 77617
29.2%
None
ValueCountFrequency (%)
 228
97.4%
à 3
 
1.3%
© 2
 
0.9%
³ 1
 
0.4%
Punctuation
ValueCountFrequency (%)
’ 149
65.4%
– 25
 
11.0%
“ 16
 
7.0%
” 16
 
7.0%
— 12
 
5.3%
‘ 10
 
4.4%

school_10th_seats
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)0.3%
Missing137
Missing (%)31.1%
Memory size21.6 KiB
2023-12-09T22:06:33.946887image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters303
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1
ValueCountFrequency (%)
1 303
100.0%
2023-12-09T22:06:34.417474image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 303
100.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 303
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 303
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 303
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 303
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 303
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 303
100.0%

academicopportunities1
Text

Distinct282
Distinct (%)64.2%
Missing1
Missing (%)0.2%
Memory size61.4 KiB
2023-12-09T22:06:34.777485image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length247
Median length140
Mean length84.63553531
Min length13

Characters and Unicode

Total characters37155
Distinct characters71
Distinct categories9 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique261 ?
Unique (%)59.5%

Sample

1st rowFree college courses at neighboring universities
2nd rowLearning to Work, Student Council, Advisory Leadership, School Newspaper, Community Service Group, School Leadership Team, Extended Day/PM School, College Now
3rd rowGenetic Research Seminar, Touro College Partnership, L'Oreal Roll Model Program, Town Halls, Laptop carts, SMART Boards in every room, Regents Prep.
4th rowCTE program(s) in: Arts, A/V Technology & Communication
5th rowCulturally relevant practices; Blended instruction with both teacher-led classes and use of digital resources
ValueCountFrequency (%)
and 263
 
5.5%
in 156
 
3.2%
college 131
 
2.7%
for 129
 
2.7%
program 119
 
2.5%
cte 112
 
2.3%
program(s 107
 
2.2%
learning 88
 
1.8%
online 73
 
1.5%
70
 
1.5%
Other values (941) 3559
74.0%
2023-12-09T22:06:35.336921image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4369
 
11.8%
e 3285
 
8.8%
n 2494
 
6.7%
r 2441
 
6.6%
o 2298
 
6.2%
a 2297
 
6.2%
i 2127
 
5.7%
s 1891
 
5.1%
t 1647
 
4.4%
l 1291
 
3.5%
Other values (61) 13015
35.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 27655
74.4%
Space Separator 4369
 
11.8%
Uppercase Letter 3521
 
9.5%
Other Punctuation 1062
 
2.9%
Dash Punctuation 174
 
0.5%
Open Punctuation 166
 
0.4%
Close Punctuation 166
 
0.4%
Decimal Number 39
 
0.1%
Final Punctuation 3
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 3285
11.9%
n 2494
 
9.0%
r 2441
 
8.8%
o 2298
 
8.3%
a 2297
 
8.3%
i 2127
 
7.7%
s 1891
 
6.8%
t 1647
 
6.0%
l 1291
 
4.7%
c 1215
 
4.4%
Other values (16) 6669
24.1%
Uppercase Letter
ValueCountFrequency (%)
C 566
16.1%
P 391
11.1%
A 329
9.3%
S 294
 
8.3%
T 293
 
8.3%
E 245
 
7.0%
L 187
 
5.3%
N 168
 
4.8%
M 137
 
3.9%
Y 123
 
3.5%
Other values (16) 788
22.4%
Other Punctuation
ValueCountFrequency (%)
, 632
59.5%
: 207
 
19.5%
& 68
 
6.4%
; 52
 
4.9%
. 52
 
4.9%
/ 47
 
4.4%
' 4
 
0.4%
Decimal Number
ValueCountFrequency (%)
1 19
48.7%
2 6
 
15.4%
0 6
 
15.4%
9 4
 
10.3%
4 2
 
5.1%
7 1
 
2.6%
6 1
 
2.6%
Space Separator
ValueCountFrequency (%)
4369
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 174
100.0%
Open Punctuation
ValueCountFrequency (%)
( 166
100.0%
Close Punctuation
ValueCountFrequency (%)
) 166
100.0%
Final Punctuation
ValueCountFrequency (%)
’ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 31176
83.9%
Common 5979
 
16.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 3285
 
10.5%
n 2494
 
8.0%
r 2441
 
7.8%
o 2298
 
7.4%
a 2297
 
7.4%
i 2127
 
6.8%
s 1891
 
6.1%
t 1647
 
5.3%
l 1291
 
4.1%
c 1215
 
3.9%
Other values (42) 10190
32.7%
Common
ValueCountFrequency (%)
4369
73.1%
, 632
 
10.6%
: 207
 
3.5%
- 174
 
2.9%
( 166
 
2.8%
) 166
 
2.8%
& 68
 
1.1%
; 52
 
0.9%
. 52
 
0.9%
/ 47
 
0.8%
Other values (9) 46
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 37149
> 99.9%
Punctuation 3
 
< 0.1%
None 3
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4369
 
11.8%
e 3285
 
8.8%
n 2494
 
6.7%
r 2441
 
6.6%
o 2298
 
6.2%
a 2297
 
6.2%
i 2127
 
5.7%
s 1891
 
5.1%
t 1647
 
4.4%
l 1291
 
3.5%
Other values (59) 13009
35.0%
Punctuation
ValueCountFrequency (%)
’ 3
100.0%
None
ValueCountFrequency (%)
 3
100.0%

academicopportunities2
Text

MISSING 

Distinct368
Distinct (%)87.0%
Missing17
Missing (%)3.9%
Memory size66.5 KiB
2023-12-09T22:06:35.726885image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length418
Median length128
Mean length98.17966903
Min length11

Characters and Unicode

Total characters41530
Distinct characters79
Distinct categories11 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique365 ?
Unique (%)86.3%

Sample

1st rowInternational Travel, Special Arts Programs, Music, Internships, College Mentoring English Language Learner Programs: English as a New Language
2nd rowCAMBA, Diploma Plus, Medgar Evers College, Coney Island Genera on Gap, Urban Neighborhood Services, Coney Island Coalition Against Violence, I Love My Life Initiative, New York City Police Department
3rd rowWAE Bucks Incentive Program, Monroe College JumpStart, National Hispanic Honor Society, National Honor Society,Lehman College Now, Castle Learning.
4th rowiLearnNYC: Program for expanded online coursework and self-paced learning
5th rowReal-world problem-based learning, Student choice on elective courses; CORE advisory program focused on personal and social development
ValueCountFrequency (%)
and 298
 
5.5%
college 195
 
3.6%
program 123
 
2.3%
for 100
 
1.8%
in 99
 
1.8%
learning 86
 
1.6%
online 70
 
1.3%
now 66
 
1.2%
of 64
 
1.2%
courses 59
 
1.1%
Other values (1263) 4273
78.6%
2023-12-09T22:06:36.320315image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5010
 
12.1%
e 3783
 
9.1%
r 2741
 
6.6%
n 2652
 
6.4%
o 2553
 
6.1%
a 2528
 
6.1%
i 2384
 
5.7%
s 2038
 
4.9%
t 1984
 
4.8%
l 1610
 
3.9%
Other values (69) 14247
34.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 31036
74.7%
Space Separator 5010
 
12.1%
Uppercase Letter 3851
 
9.3%
Other Punctuation 1192
 
2.9%
Dash Punctuation 195
 
0.5%
Decimal Number 87
 
0.2%
Close Punctuation 71
 
0.2%
Open Punctuation 71
 
0.2%
Final Punctuation 12
 
< 0.1%
Initial Punctuation 3
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
C 600
15.6%
A 374
 
9.7%
P 356
 
9.2%
S 345
 
9.0%
N 250
 
6.5%
T 242
 
6.3%
E 206
 
5.3%
L 196
 
5.1%
Y 148
 
3.8%
M 136
 
3.5%
Other values (17) 998
25.9%
Lowercase Letter
ValueCountFrequency (%)
e 3783
12.2%
r 2741
 
8.8%
n 2652
 
8.5%
o 2553
 
8.2%
a 2528
 
8.1%
i 2384
 
7.7%
s 2038
 
6.6%
t 1984
 
6.4%
l 1610
 
5.2%
c 1353
 
4.4%
Other values (16) 7410
23.9%
Decimal Number
ValueCountFrequency (%)
1 38
43.7%
0 18
20.7%
2 13
 
14.9%
3 6
 
6.9%
9 4
 
4.6%
4 3
 
3.4%
8 2
 
2.3%
5 2
 
2.3%
6 1
 
1.1%
Other Punctuation
ValueCountFrequency (%)
, 890
74.7%
: 110
 
9.2%
; 76
 
6.4%
. 50
 
4.2%
& 32
 
2.7%
/ 30
 
2.5%
' 3
 
0.3%
! 1
 
0.1%
Final Punctuation
ValueCountFrequency (%)
’ 11
91.7%
” 1
 
8.3%
Initial Punctuation
ValueCountFrequency (%)
‘ 2
66.7%
“ 1
33.3%
Space Separator
ValueCountFrequency (%)
5010
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 195
100.0%
Close Punctuation
ValueCountFrequency (%)
) 71
100.0%
Open Punctuation
ValueCountFrequency (%)
( 71
100.0%
Math Symbol
ValueCountFrequency (%)
+ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 34887
84.0%
Common 6643
 
16.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 3783
 
10.8%
r 2741
 
7.9%
n 2652
 
7.6%
o 2553
 
7.3%
a 2528
 
7.2%
i 2384
 
6.8%
s 2038
 
5.8%
t 1984
 
5.7%
l 1610
 
4.6%
c 1353
 
3.9%
Other values (43) 11261
32.3%
Common
ValueCountFrequency (%)
5010
75.4%
, 890
 
13.4%
- 195
 
2.9%
: 110
 
1.7%
; 76
 
1.1%
) 71
 
1.1%
( 71
 
1.1%
. 50
 
0.8%
1 38
 
0.6%
& 32
 
0.5%
Other values (16) 100
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 41500
99.9%
None 15
 
< 0.1%
Punctuation 15
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5010
 
12.1%
e 3783
 
9.1%
r 2741
 
6.6%
n 2652
 
6.4%
o 2553
 
6.2%
a 2528
 
6.1%
i 2384
 
5.7%
s 2038
 
4.9%
t 1984
 
4.8%
l 1610
 
3.9%
Other values (64) 14217
34.3%
None
ValueCountFrequency (%)
 15
100.0%
Punctuation
ValueCountFrequency (%)
’ 11
73.3%
‘ 2
 
13.3%
” 1
 
6.7%
“ 1
 
6.7%

academicopportunities3
Text

MISSING 

Distinct378
Distinct (%)99.0%
Missing58
Missing (%)13.2%
Memory size61.4 KiB
2023-12-09T22:06:36.662563image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length154
Median length115
Mean length97.23036649
Min length9

Characters and Unicode

Total characters37142
Distinct characters80
Distinct categories12 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique374 ?
Unique (%)97.9%

Sample

1st rowThe Learning to Work (LTW) partner for Liberation Diploma Plus High School is CAMBA.
2nd rowPupilpath, Saturday school, Leadership class, College Trips, Teen Empowerment Series, College Fairs, Anti-bullying Day, Respect for All, Career Day.
3rd rowWe offer highly competitive positions in our Drama, Chorus, and Dance Company classes
4th rowMentoring; Rites of passage experiences; College and career counseling starting in ninth grade; Internships; College-level courses in upper grades
5th rowStudents prepare for college entrance exams with CUNY At Home in College Classes and earn college credit
ValueCountFrequency (%)
and 220
 
4.4%
college 178
 
3.6%
program 92
 
1.8%
in 91
 
1.8%
the 72
 
1.4%
courses 68
 
1.4%
of 64
 
1.3%
for 60
 
1.2%
students 60
 
1.2%
to 55
 
1.1%
Other values (1309) 4041
80.8%
2023-12-09T22:06:37.195070image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4619
 
12.4%
e 3414
 
9.2%
r 2269
 
6.1%
n 2258
 
6.1%
o 2193
 
5.9%
i 2193
 
5.9%
a 2131
 
5.7%
t 1997
 
5.4%
s 1871
 
5.0%
l 1409
 
3.8%
Other values (70) 12788
34.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 27565
74.2%
Space Separator 4619
 
12.4%
Uppercase Letter 3626
 
9.8%
Other Punctuation 1003
 
2.7%
Dash Punctuation 105
 
0.3%
Close Punctuation 68
 
0.2%
Open Punctuation 68
 
0.2%
Decimal Number 66
 
0.2%
Final Punctuation 14
 
< 0.1%
Math Symbol 6
 
< 0.1%
Other values (2) 2
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
C 505
13.9%
S 400
11.0%
A 376
 
10.4%
P 320
 
8.8%
T 218
 
6.0%
E 212
 
5.8%
N 183
 
5.0%
M 157
 
4.3%
I 147
 
4.1%
D 121
 
3.3%
Other values (17) 987
27.2%
Lowercase Letter
ValueCountFrequency (%)
e 3414
12.4%
r 2269
 
8.2%
n 2258
 
8.2%
o 2193
 
8.0%
i 2193
 
8.0%
a 2131
 
7.7%
t 1997
 
7.2%
s 1871
 
6.8%
l 1409
 
5.1%
c 1204
 
4.4%
Other values (16) 6626
24.0%
Decimal Number
ValueCountFrequency (%)
1 30
45.5%
0 10
 
15.2%
2 9
 
13.6%
3 6
 
9.1%
9 3
 
4.5%
8 2
 
3.0%
4 2
 
3.0%
5 2
 
3.0%
6 1
 
1.5%
7 1
 
1.5%
Other Punctuation
ValueCountFrequency (%)
, 751
74.9%
; 91
 
9.1%
. 53
 
5.3%
: 53
 
5.3%
& 31
 
3.1%
/ 21
 
2.1%
' 2
 
0.2%
! 1
 
0.1%
Dash Punctuation
ValueCountFrequency (%)
- 104
99.0%
– 1
 
1.0%
Space Separator
ValueCountFrequency (%)
4619
100.0%
Close Punctuation
ValueCountFrequency (%)
) 68
100.0%
Open Punctuation
ValueCountFrequency (%)
( 68
100.0%
Final Punctuation
ValueCountFrequency (%)
’ 14
100.0%
Math Symbol
ValueCountFrequency (%)
+ 6
100.0%
Initial Punctuation
ValueCountFrequency (%)
‘ 1
100.0%
Other Symbol
ValueCountFrequency (%)
® 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 31191
84.0%
Common 5951
 
16.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 3414
 
10.9%
r 2269
 
7.3%
n 2258
 
7.2%
o 2193
 
7.0%
i 2193
 
7.0%
a 2131
 
6.8%
t 1997
 
6.4%
s 1871
 
6.0%
l 1409
 
4.5%
c 1204
 
3.9%
Other values (43) 10252
32.9%
Common
ValueCountFrequency (%)
4619
77.6%
, 751
 
12.6%
- 104
 
1.7%
; 91
 
1.5%
) 68
 
1.1%
( 68
 
1.1%
. 53
 
0.9%
: 53
 
0.9%
& 31
 
0.5%
1 30
 
0.5%
Other values (17) 83
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 37108
99.9%
None 18
 
< 0.1%
Punctuation 16
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4619
 
12.4%
e 3414
 
9.2%
r 2269
 
6.1%
n 2258
 
6.1%
o 2193
 
5.9%
i 2193
 
5.9%
a 2131
 
5.7%
t 1997
 
5.4%
s 1871
 
5.0%
l 1409
 
3.8%
Other values (65) 12754
34.4%
None
ValueCountFrequency (%)
 17
94.4%
® 1
 
5.6%
Punctuation
ValueCountFrequency (%)
’ 14
87.5%
– 1
 
6.2%
‘ 1
 
6.2%

academicopportunities4
Text

MISSING 

Distinct310
Distinct (%)99.4%
Missing128
Missing (%)29.1%
Memory size53.0 KiB
2023-12-09T22:06:37.526944image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length189
Median length120
Mean length98.51602564
Min length8

Characters and Unicode

Total characters30737
Distinct characters75
Distinct categories10 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique309 ?
Unique (%)99.0%

Sample

1st rowPEARLS Awards, Academy Awards, Rose Ceremony/Parent Daughter Breakfast, Ice Cream Social.
2nd rowStudents receive small group instruction focused on sharpening their skills while developing their professional portfolio for auditions
3rd rowGuest Speaker Series
4th rowThe International Academy is a dynamic community of ELL's from over 30 countries taking courses intended to prepare them to be College/Career ready.
5th rowIn 10th grade, students choose one of the CTE pathways in the Building Arts (Carpentry, Masonry, Decorative Finishing) or Landscape Management.
ValueCountFrequency (%)
and 202
 
4.9%
college 147
 
3.6%
in 62
 
1.5%
program 57
 
1.4%
to 56
 
1.4%
of 52
 
1.3%
for 51
 
1.2%
the 48
 
1.2%
cuny 46
 
1.1%
with 45
 
1.1%
Other values (1199) 3346
81.4%
2023-12-09T22:06:38.048095image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3802
 
12.4%
e 2746
 
8.9%
i 1875
 
6.1%
o 1869
 
6.1%
r 1868
 
6.1%
n 1859
 
6.0%
a 1779
 
5.8%
t 1755
 
5.7%
s 1557
 
5.1%
l 1124
 
3.7%
Other values (65) 10503
34.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 22938
74.6%
Space Separator 3802
 
12.4%
Uppercase Letter 2900
 
9.4%
Other Punctuation 830
 
2.7%
Dash Punctuation 104
 
0.3%
Open Punctuation 54
 
0.2%
Close Punctuation 54
 
0.2%
Decimal Number 44
 
0.1%
Final Punctuation 9
 
< 0.1%
Math Symbol 2
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
C 430
14.8%
S 336
11.6%
A 289
 
10.0%
P 230
 
7.9%
T 180
 
6.2%
N 157
 
5.4%
E 150
 
5.2%
M 148
 
5.1%
I 105
 
3.6%
L 99
 
3.4%
Other values (17) 776
26.8%
Lowercase Letter
ValueCountFrequency (%)
e 2746
12.0%
i 1875
 
8.2%
o 1869
 
8.1%
r 1868
 
8.1%
n 1859
 
8.1%
a 1779
 
7.8%
t 1755
 
7.7%
s 1557
 
6.8%
l 1124
 
4.9%
c 961
 
4.2%
Other values (16) 5545
24.2%
Other Punctuation
ValueCountFrequency (%)
, 611
73.6%
; 95
 
11.4%
. 41
 
4.9%
: 33
 
4.0%
& 27
 
3.3%
/ 17
 
2.0%
' 4
 
0.5%
@ 1
 
0.1%
! 1
 
0.1%
Decimal Number
ValueCountFrequency (%)
1 21
47.7%
2 11
25.0%
0 6
 
13.6%
4 3
 
6.8%
9 2
 
4.5%
3 1
 
2.3%
Dash Punctuation
ValueCountFrequency (%)
- 101
97.1%
— 3
 
2.9%
Space Separator
ValueCountFrequency (%)
3802
100.0%
Open Punctuation
ValueCountFrequency (%)
( 54
100.0%
Close Punctuation
ValueCountFrequency (%)
) 54
100.0%
Final Punctuation
ValueCountFrequency (%)
’ 9
100.0%
Math Symbol
ValueCountFrequency (%)
+ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 25838
84.1%
Common 4899
 
15.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 2746
 
10.6%
i 1875
 
7.3%
o 1869
 
7.2%
r 1868
 
7.2%
n 1859
 
7.2%
a 1779
 
6.9%
t 1755
 
6.8%
s 1557
 
6.0%
l 1124
 
4.4%
c 961
 
3.7%
Other values (43) 8445
32.7%
Common
ValueCountFrequency (%)
3802
77.6%
, 611
 
12.5%
- 101
 
2.1%
; 95
 
1.9%
( 54
 
1.1%
) 54
 
1.1%
. 41
 
0.8%
: 33
 
0.7%
& 27
 
0.6%
1 21
 
0.4%
Other values (12) 60
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 30713
99.9%
None 12
 
< 0.1%
Punctuation 12
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3802
 
12.4%
e 2746
 
8.9%
i 1875
 
6.1%
o 1869
 
6.1%
r 1868
 
6.1%
n 1859
 
6.1%
a 1779
 
5.8%
t 1755
 
5.7%
s 1557
 
5.1%
l 1124
 
3.7%
Other values (62) 10479
34.1%
None
ValueCountFrequency (%)
 12
100.0%
Punctuation
ValueCountFrequency (%)
’ 9
75.0%
— 3
 
25.0%

academicopportunities5
Text

MISSING 

Distinct183
Distinct (%)100.0%
Missing257
Missing (%)58.4%
Memory size36.7 KiB
2023-12-09T22:06:38.461512image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length163
Median length122
Mean length98.32786885
Min length7

Characters and Unicode

Total characters17994
Distinct characters75
Distinct categories9 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique183 ?
Unique (%)100.0%

Sample

1st rowHealth and Wellness Program
2nd rowThe Law Pathway educates students about the law and its applications while empowering them with the skills needed for careers in the legal field.
3rd rowJuniors and seniors complete paid internships with the National Park Service, National Parks of NY Harbor, and Prospect Park.
4th rowAdvisory system ensures that we know every student well and have a strong connection with their families
5th rowCUNY College Now, Creative Writing, Yoga, Weight Training, Internships
ValueCountFrequency (%)
and 129
 
5.4%
college 96
 
4.0%
the 38
 
1.6%
program 38
 
1.6%
now 32
 
1.3%
cuny 30
 
1.3%
in 30
 
1.3%
students 25
 
1.1%
arts 25
 
1.1%
prep 25
 
1.1%
Other values (903) 1908
80.3%
2023-12-09T22:06:39.057446image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2193
 
12.2%
e 1660
 
9.2%
r 1108
 
6.2%
o 1059
 
5.9%
a 1047
 
5.8%
n 1032
 
5.7%
i 1020
 
5.7%
t 995
 
5.5%
s 900
 
5.0%
l 667
 
3.7%
Other values (65) 6313
35.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 13243
73.6%
Space Separator 2193
 
12.2%
Uppercase Letter 1848
 
10.3%
Other Punctuation 548
 
3.0%
Dash Punctuation 56
 
0.3%
Decimal Number 39
 
0.2%
Open Punctuation 31
 
0.2%
Close Punctuation 31
 
0.2%
Final Punctuation 5
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 1660
12.5%
r 1108
 
8.4%
o 1059
 
8.0%
a 1047
 
7.9%
n 1032
 
7.8%
i 1020
 
7.7%
t 995
 
7.5%
s 900
 
6.8%
l 667
 
5.0%
c 572
 
4.3%
Other values (16) 3183
24.0%
Uppercase Letter
ValueCountFrequency (%)
C 292
15.8%
S 189
 
10.2%
A 180
 
9.7%
P 155
 
8.4%
T 120
 
6.5%
N 118
 
6.4%
E 90
 
4.9%
M 74
 
4.0%
I 71
 
3.8%
L 64
 
3.5%
Other values (16) 495
26.8%
Decimal Number
ValueCountFrequency (%)
1 16
41.0%
2 8
20.5%
0 5
 
12.8%
6 3
 
7.7%
5 2
 
5.1%
3 2
 
5.1%
8 1
 
2.6%
9 1
 
2.6%
4 1
 
2.6%
Other Punctuation
ValueCountFrequency (%)
, 417
76.1%
; 53
 
9.7%
. 34
 
6.2%
/ 16
 
2.9%
: 14
 
2.6%
& 12
 
2.2%
' 1
 
0.2%
! 1
 
0.2%
Dash Punctuation
ValueCountFrequency (%)
- 54
96.4%
— 2
 
3.6%
Space Separator
ValueCountFrequency (%)
2193
100.0%
Open Punctuation
ValueCountFrequency (%)
( 31
100.0%
Close Punctuation
ValueCountFrequency (%)
) 31
100.0%
Final Punctuation
ValueCountFrequency (%)
’ 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 15091
83.9%
Common 2903
 
16.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 1660
 
11.0%
r 1108
 
7.3%
o 1059
 
7.0%
a 1047
 
6.9%
n 1032
 
6.8%
i 1020
 
6.8%
t 995
 
6.6%
s 900
 
6.0%
l 667
 
4.4%
c 572
 
3.8%
Other values (42) 5031
33.3%
Common
ValueCountFrequency (%)
2193
75.5%
, 417
 
14.4%
- 54
 
1.9%
; 53
 
1.8%
. 34
 
1.2%
( 31
 
1.1%
) 31
 
1.1%
1 16
 
0.6%
/ 16
 
0.6%
: 14
 
0.5%
Other values (13) 44
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 17980
99.9%
None 7
 
< 0.1%
Punctuation 7
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2193
 
12.2%
e 1660
 
9.2%
r 1108
 
6.2%
o 1059
 
5.9%
a 1047
 
5.8%
n 1032
 
5.7%
i 1020
 
5.7%
t 995
 
5.5%
s 900
 
5.0%
l 667
 
3.7%
Other values (62) 6299
35.0%
None
ValueCountFrequency (%)
 7
100.0%
Punctuation
ValueCountFrequency (%)
’ 5
71.4%
— 2
 
28.6%

ell_programs
Text

Distinct11
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size37.9 KiB
2023-12-09T22:06:39.281806image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length115
Median length25
Mean length30.84772727
Min length25

Characters and Unicode

Total characters13573
Distinct characters33
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)1.1%

Sample

1st rowEnglish as a New Language
2nd rowEnglish as a New Language
3rd rowEnglish as a New Language
4th rowEnglish as a New Language
5th rowEnglish as a New Language
ValueCountFrequency (%)
language 453
18.5%
english 440
17.9%
as 440
17.9%
a 440
17.9%
new 440
17.9%
spanish 54
 
2.2%
bilingual 50
 
2.0%
education 50
 
2.0%
transitional 50
 
2.0%
chinese 14
 
0.6%
Other values (7) 21
 
0.9%
2023-12-09T22:06:39.646456image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 2060
15.2%
2012
14.8%
g 1397
10.3%
n 1166
8.6%
s 1000
 
7.4%
e 927
 
6.8%
i 765
 
5.6%
l 606
 
4.5%
u 567
 
4.2%
h 509
 
3.8%
Other values (23) 2564
18.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 9852
72.6%
Space Separator 2012
 
14.8%
Uppercase Letter 1572
 
11.6%
Other Punctuation 137
 
1.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 2060
20.9%
g 1397
14.2%
n 1166
11.8%
s 1000
10.2%
e 927
9.4%
i 765
 
7.8%
l 606
 
6.2%
u 567
 
5.8%
h 509
 
5.2%
w 440
 
4.5%
Other values (7) 415
 
4.2%
Uppercase Letter
ValueCountFrequency (%)
E 490
31.2%
L 453
28.8%
N 440
28.0%
S 54
 
3.4%
B 51
 
3.2%
T 50
 
3.2%
C 16
 
1.0%
D 13
 
0.8%
H 2
 
0.1%
A 1
 
0.1%
Other values (2) 2
 
0.1%
Other Punctuation
ValueCountFrequency (%)
: 63
46.0%
; 63
46.0%
, 11
 
8.0%
Space Separator
ValueCountFrequency (%)
2012
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 11424
84.2%
Common 2149
 
15.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 2060
18.0%
g 1397
12.2%
n 1166
10.2%
s 1000
8.8%
e 927
8.1%
i 765
 
6.7%
l 606
 
5.3%
u 567
 
5.0%
h 509
 
4.5%
E 490
 
4.3%
Other values (19) 1937
17.0%
Common
ValueCountFrequency (%)
2012
93.6%
: 63
 
2.9%
; 63
 
2.9%
, 11
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 13573
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 2060
15.2%
2012
14.8%
g 1397
10.3%
n 1166
8.6%
s 1000
 
7.4%
e 927
 
6.8%
i 765
 
5.6%
l 606
 
4.5%
u 567
 
4.2%
h 509
 
3.8%
Other values (23) 2564
18.9%

language_classes
Text

MISSING 

Distinct72
Distinct (%)17.1%
Missing18
Missing (%)4.1%
Memory size30.9 KiB
2023-12-09T22:06:39.857653image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length159
Median length7
Mean length16.30805687
Min length6

Characters and Unicode

Total characters6882
Distinct characters42
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique51 ?
Unique (%)12.1%

Sample

1st rowFrench, Spanish
2nd rowSpanish
3rd rowSpanish
4th rowFrench, Spanish
5th rowFrench
ValueCountFrequency (%)
spanish 401
45.7%
french 129
 
14.7%
italian 57
 
6.5%
chinese 49
 
5.6%
mandarin 45
 
5.1%
japanese 29
 
3.3%
latin 25
 
2.8%
american 20
 
2.3%
sign 20
 
2.3%
language 20
 
2.3%
Other values (18) 83
 
9.5%
2023-12-09T22:06:40.256261image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
n 891
12.9%
a 808
11.7%
i 662
9.6%
h 582
8.5%
s 508
 
7.4%
456
 
6.6%
p 430
 
6.2%
S 421
 
6.1%
e 397
 
5.8%
, 364
 
5.3%
Other values (32) 1363
19.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 5086
73.9%
Uppercase Letter 878
 
12.8%
Space Separator 456
 
6.6%
Other Punctuation 364
 
5.3%
Open Punctuation 49
 
0.7%
Close Punctuation 49
 
0.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n 891
17.5%
a 808
15.9%
i 662
13.0%
h 582
11.4%
s 508
10.0%
p 430
8.5%
e 397
7.8%
r 247
 
4.9%
c 163
 
3.2%
t 93
 
1.8%
Other values (10) 305
 
6.0%
Uppercase Letter
ValueCountFrequency (%)
S 421
47.9%
F 129
 
14.7%
I 57
 
6.5%
C 56
 
6.4%
M 45
 
5.1%
L 45
 
5.1%
A 33
 
3.8%
J 29
 
3.3%
G 21
 
2.4%
R 10
 
1.1%
Other values (8) 32
 
3.6%
Space Separator
ValueCountFrequency (%)
456
100.0%
Other Punctuation
ValueCountFrequency (%)
, 364
100.0%
Open Punctuation
ValueCountFrequency (%)
( 49
100.0%
Close Punctuation
ValueCountFrequency (%)
) 49
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 5964
86.7%
Common 918
 
13.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
n 891
14.9%
a 808
13.5%
i 662
11.1%
h 582
9.8%
s 508
8.5%
p 430
7.2%
S 421
7.1%
e 397
6.7%
r 247
 
4.1%
c 163
 
2.7%
Other values (28) 855
14.3%
Common
ValueCountFrequency (%)
456
49.7%
, 364
39.7%
( 49
 
5.3%
) 49
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6882
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n 891
12.9%
a 808
11.7%
i 662
9.6%
h 582
8.5%
s 508
 
7.4%
456
 
6.6%
p 430
 
6.2%
S 421
 
6.1%
e 397
 
5.8%
, 364
 
5.3%
Other values (32) 1363
19.8%

advancedplacement_courses
Text

MISSING 

Distinct225
Distinct (%)70.5%
Missing121
Missing (%)27.5%
Memory size43.4 KiB
2023-12-09T22:06:40.463353image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length320
Median length183
Mean length69.81191223
Min length10

Characters and Unicode

Total characters22270
Distinct characters36
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique191 ?
Unique (%)59.9%

Sample

1st rowAP English, AP Environmental Science, AP US History
2nd rowAP Biology, AP English, AP Environmental Science, AP Statistics, AP US History, AP World History
3rd rowAP Art History
4th rowAP Environmental Science, AP Spanish
5th rowAP English, AP US Government and Politics
ValueCountFrequency (%)
ap 1468
40.4%
history 282
 
7.8%
english 265
 
7.3%
us 237
 
6.5%
calculus 141
 
3.9%
biology 127
 
3.5%
science 119
 
3.3%
spanish 107
 
2.9%
environmental 95
 
2.6%
world 79
 
2.2%
Other values (23) 713
19.6%
2023-12-09T22:06:40.875303image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3318
14.9%
P 1639
 
7.4%
A 1508
 
6.8%
i 1483
 
6.7%
s 1260
 
5.7%
, 1149
 
5.2%
o 1149
 
5.2%
n 1127
 
5.1%
l 982
 
4.4%
t 883
 
4.0%
Other values (26) 7772
34.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 12543
56.3%
Uppercase Letter 5260
23.6%
Space Separator 3318
 
14.9%
Other Punctuation 1149
 
5.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i 1483
11.8%
s 1260
10.0%
o 1149
 
9.2%
n 1127
 
9.0%
l 982
 
7.8%
t 883
 
7.0%
r 730
 
5.8%
c 705
 
5.6%
e 693
 
5.5%
y 645
 
5.1%
Other values (8) 2886
23.0%
Uppercase Letter
ValueCountFrequency (%)
P 1639
31.2%
A 1508
28.7%
S 551
 
10.5%
E 412
 
7.8%
H 302
 
5.7%
C 247
 
4.7%
U 237
 
4.5%
B 127
 
2.4%
G 99
 
1.9%
W 79
 
1.5%
Other values (6) 59
 
1.1%
Space Separator
ValueCountFrequency (%)
3318
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1149
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 17803
79.9%
Common 4467
 
20.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
P 1639
 
9.2%
A 1508
 
8.5%
i 1483
 
8.3%
s 1260
 
7.1%
o 1149
 
6.5%
n 1127
 
6.3%
l 982
 
5.5%
t 883
 
5.0%
r 730
 
4.1%
c 705
 
4.0%
Other values (24) 6337
35.6%
Common
ValueCountFrequency (%)
3318
74.3%
, 1149
 
25.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 22270
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3318
14.9%
P 1639
 
7.4%
A 1508
 
6.8%
i 1483
 
6.7%
s 1260
 
5.7%
, 1149
 
5.2%
o 1149
 
5.2%
n 1127
 
5.1%
l 982
 
4.4%
t 883
 
4.0%
Other values (26) 7772
34.9%

diplomaendorsements
Text

MISSING 

Distinct11
Distinct (%)9.4%
Missing323
Missing (%)73.4%
Memory size17.8 KiB
2023-12-09T22:06:41.044200image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length24
Median length18
Mean length9.111111111
Min length3

Characters and Unicode

Total characters1066
Distinct characters17
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)1.7%

Sample

1st rowScience
2nd rowMath
3rd rowMath, Science
4th rowArts, Math, Science
5th rowScience
ValueCountFrequency (%)
science 63
32.8%
math 59
30.7%
cte 41
21.4%
arts 29
15.1%
2023-12-09T22:06:41.370172image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 126
11.8%
c 126
11.8%
t 88
 
8.3%
, 75
 
7.0%
75
 
7.0%
i 63
 
5.9%
n 63
 
5.9%
S 63
 
5.9%
M 59
 
5.5%
a 59
 
5.5%
Other values (7) 269
25.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 642
60.2%
Uppercase Letter 274
25.7%
Other Punctuation 75
 
7.0%
Space Separator 75
 
7.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 126
19.6%
c 126
19.6%
t 88
13.7%
i 63
9.8%
n 63
9.8%
a 59
9.2%
h 59
9.2%
r 29
 
4.5%
s 29
 
4.5%
Uppercase Letter
ValueCountFrequency (%)
S 63
23.0%
M 59
21.5%
C 41
15.0%
T 41
15.0%
E 41
15.0%
A 29
10.6%
Other Punctuation
ValueCountFrequency (%)
, 75
100.0%
Space Separator
ValueCountFrequency (%)
75
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 916
85.9%
Common 150
 
14.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 126
13.8%
c 126
13.8%
t 88
9.6%
i 63
 
6.9%
n 63
 
6.9%
S 63
 
6.9%
M 59
 
6.4%
a 59
 
6.4%
h 59
 
6.4%
C 41
 
4.5%
Other values (5) 169
18.4%
Common
ValueCountFrequency (%)
, 75
50.0%
75
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1066
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 126
11.8%
c 126
11.8%
t 88
 
8.3%
, 75
 
7.0%
75
 
7.0%
i 63
 
5.9%
n 63
 
5.9%
S 63
 
5.9%
M 59
 
5.5%
a 59
 
5.5%
Other values (7) 269
25.2%

neighborhood
Text

Distinct119
Distinct (%)27.0%
Missing0
Missing (%)0.0%
Memory size31.5 KiB
2023-12-09T22:06:41.735088image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length33
Median length23
Mean length16.025
Min length6

Characters and Unicode

Total characters7051
Distinct characters52
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique36 ?
Unique (%)8.2%

Sample

1st rowChelsea-Union Sq
2nd rowSeagate-Coney Island
3rd rowCastle Hill-Clason Point
4th rowCrown Heights South
5th rowSouth Ozone Park
ValueCountFrequency (%)
east 33
 
3.8%
village 28
 
3.3%
heights 24
 
2.8%
hills 20
 
2.3%
park 19
 
2.2%
west 18
 
2.1%
south 16
 
1.9%
gardens 15
 
1.7%
north 15
 
1.7%
clinton 14
 
1.6%
Other values (141) 657
76.5%
2023-12-09T22:06:42.261445image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 533
 
7.6%
a 486
 
6.9%
o 482
 
6.8%
n 481
 
6.8%
l 443
 
6.3%
r 438
 
6.2%
419
 
5.9%
i 411
 
5.8%
t 406
 
5.8%
s 375
 
5.3%
Other values (42) 2577
36.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 5362
76.0%
Uppercase Letter 1077
 
15.3%
Space Separator 419
 
5.9%
Dash Punctuation 158
 
2.2%
Other Punctuation 35
 
0.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 533
9.9%
a 486
9.1%
o 482
9.0%
n 481
9.0%
l 443
 
8.3%
r 438
 
8.2%
i 411
 
7.7%
t 406
 
7.6%
s 375
 
7.0%
h 172
 
3.2%
Other values (15) 1135
21.2%
Uppercase Letter
ValueCountFrequency (%)
C 147
13.6%
H 122
11.3%
B 119
11.0%
S 95
 
8.8%
M 72
 
6.7%
P 57
 
5.3%
E 49
 
4.5%
N 46
 
4.3%
W 46
 
4.3%
G 40
 
3.7%
Other values (14) 284
26.4%
Space Separator
ValueCountFrequency (%)
419
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 158
100.0%
Other Punctuation
ValueCountFrequency (%)
. 35
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 6439
91.3%
Common 612
 
8.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 533
 
8.3%
a 486
 
7.5%
o 482
 
7.5%
n 481
 
7.5%
l 443
 
6.9%
r 438
 
6.8%
i 411
 
6.4%
t 406
 
6.3%
s 375
 
5.8%
h 172
 
2.7%
Other values (39) 2212
34.4%
Common
ValueCountFrequency (%)
419
68.5%
- 158
 
25.8%
. 35
 
5.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7051
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 533
 
7.6%
a 486
 
6.9%
o 482
 
6.8%
n 481
 
6.8%
l 443
 
6.3%
r 438
 
6.2%
419
 
5.9%
i 411
 
5.8%
t 406
 
5.8%
s 375
 
5.3%
Other values (42) 2577
36.5%

shared_space
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)0.3%
Missing70
Missing (%)15.9%
Memory size24.0 KiB
2023-12-09T22:06:42.394944image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters1110
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowYes
2nd rowYes
3rd rowYes
4th rowYes
5th rowYes
ValueCountFrequency (%)
yes 370
100.0%
2023-12-09T22:06:42.651276image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
Y 370
33.3%
e 370
33.3%
s 370
33.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 740
66.7%
Uppercase Letter 370
33.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 370
50.0%
s 370
50.0%
Uppercase Letter
ValueCountFrequency (%)
Y 370
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1110
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
Y 370
33.3%
e 370
33.3%
s 370
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1110
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
Y 370
33.3%
e 370
33.3%
s 370
33.3%

campus_name
Text

MISSING 

Distinct61
Distinct (%)30.8%
Missing242
Missing (%)55.0%
Memory size25.0 KiB
2023-12-09T22:06:43.008416image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length41
Median length37
Mean length32.69191919
Min length22

Characters and Unicode

Total characters6473
Distinct characters46
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10 ?
Unique (%)5.1%

Sample

1st rowProspect Heights Educational Campus
2nd rowSpringfield Gardens Educational Campus
3rd rowSouth Shore Educational Campus
4th rowElmhurst Educational Campus
5th rowGraphics Educational Campus
ValueCountFrequency (%)
educational 196
24.0%
campus 195
23.9%
george 10
 
1.2%
park 10
 
1.2%
washington 9
 
1.1%
e 8
 
1.0%
john 8
 
1.0%
thomas 7
 
0.9%
h 7
 
0.9%
lehman 7
 
0.9%
Other values (108) 360
44.1%
2023-12-09T22:06:43.824912image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 798
 
12.3%
623
 
9.6%
u 453
 
7.0%
n 369
 
5.7%
o 357
 
5.5%
t 336
 
5.2%
i 321
 
5.0%
s 310
 
4.8%
l 291
 
4.5%
d 274
 
4.2%
Other values (36) 2341
36.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 4991
77.1%
Uppercase Letter 821
 
12.7%
Space Separator 623
 
9.6%
Other Punctuation 38
 
0.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 798
16.0%
u 453
 
9.1%
n 369
 
7.4%
o 357
 
7.2%
t 336
 
6.7%
i 321
 
6.4%
s 310
 
6.2%
l 291
 
5.8%
d 274
 
5.5%
m 264
 
5.3%
Other values (13) 1218
24.4%
Uppercase Letter
ValueCountFrequency (%)
C 224
27.3%
E 221
26.9%
J 39
 
4.8%
S 39
 
4.8%
H 38
 
4.6%
W 36
 
4.4%
M 29
 
3.5%
T 26
 
3.2%
L 26
 
3.2%
G 24
 
2.9%
Other values (11) 119
14.5%
Space Separator
ValueCountFrequency (%)
623
100.0%
Other Punctuation
ValueCountFrequency (%)
. 38
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 5812
89.8%
Common 661
 
10.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 798
 
13.7%
u 453
 
7.8%
n 369
 
6.3%
o 357
 
6.1%
t 336
 
5.8%
i 321
 
5.5%
s 310
 
5.3%
l 291
 
5.0%
d 274
 
4.7%
m 264
 
4.5%
Other values (34) 2039
35.1%
Common
ValueCountFrequency (%)
623
94.3%
. 38
 
5.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6473
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 798
 
12.3%
623
 
9.6%
u 453
 
7.0%
n 369
 
5.7%
o 357
 
5.5%
t 336
 
5.2%
i 321
 
5.0%
s 310
 
4.8%
l 291
 
4.5%
d 274
 
4.2%
Other values (36) 2341
36.2%

building_code
Text

Distinct259
Distinct (%)59.0%
Missing1
Missing (%)0.2%
Memory size26.3 KiB
2023-12-09T22:06:44.325032image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length4
Median length4
Mean length4
Min length4

Characters and Unicode

Total characters1756
Distinct characters15
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique176 ?
Unique (%)40.1%

Sample

1st rowM868
2nd rowK728
3rd rowX174
4th rowK440
5th rowQ226
ValueCountFrequency (%)
x425 6
 
1.4%
x435 6
 
1.4%
x450 6
 
1.4%
x405 6
 
1.4%
x410 6
 
1.4%
x430 5
 
1.1%
k465 5
 
1.1%
m490 5
 
1.1%
k420 5
 
1.1%
m460 5
 
1.1%
Other values (249) 384
87.5%
2023-12-09T22:06:44.928947image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 273
15.5%
0 254
14.5%
5 200
11.4%
K 124
 
7.1%
X 118
 
6.7%
M 107
 
6.1%
6 106
 
6.0%
2 95
 
5.4%
1 86
 
4.9%
8 81
 
4.6%
Other values (5) 312
17.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1317
75.0%
Uppercase Letter 439
 
25.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 273
20.7%
0 254
19.3%
5 200
15.2%
6 106
 
8.0%
2 95
 
7.2%
1 86
 
6.5%
8 81
 
6.2%
3 78
 
5.9%
7 78
 
5.9%
9 66
 
5.0%
Uppercase Letter
ValueCountFrequency (%)
K 124
28.2%
X 118
26.9%
M 107
24.4%
Q 80
18.2%
R 10
 
2.3%

Most occurring scripts

ValueCountFrequency (%)
Common 1317
75.0%
Latin 439
 
25.0%

Most frequent character per script

Common
ValueCountFrequency (%)
4 273
20.7%
0 254
19.3%
5 200
15.2%
6 106
 
8.0%
2 95
 
7.2%
1 86
 
6.5%
8 81
 
6.2%
3 78
 
5.9%
7 78
 
5.9%
9 66
 
5.0%
Latin
ValueCountFrequency (%)
K 124
28.2%
X 118
26.9%
M 107
24.4%
Q 80
18.2%
R 10
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1756
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 273
15.5%
0 254
14.5%
5 200
11.4%
K 124
 
7.1%
X 118
 
6.7%
M 107
 
6.1%
6 106
 
6.0%
2 95
 
5.4%
1 86
 
4.9%
8 81
 
4.6%
Other values (5) 312
17.8%

location
Text

Distinct263
Distinct (%)59.8%
Missing0
Missing (%)0.0%
Memory size51.3 KiB
2023-12-09T22:06:45.392820image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length81
Median length72
Mean length62.14090909
Min length43

Characters and Unicode

Total characters27342
Distinct characters67
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique183 ?
Unique (%)41.6%

Sample

1st row10 East 15th Street, Manhattan NY 10003 (40.736526, -73.992727)
2nd row2865 West 19th Street, Brooklyn, NY 11224 (40.576976, -73.985413)
3rd row456 White Plains Road, Bronx NY 10473 (40.815043, -73.85607)
4th row883 Classon Avenue, Brooklyn NY 11225 (40.669805, -73.960689)
5th row121-10 Rockaway Boulevard, South Ozone Park NY 11420 (40.675021, -73.81673)
ValueCountFrequency (%)
ny 440
 
11.8%
avenue 188
 
5.0%
street 166
 
4.4%
brooklyn 123
 
3.3%
bronx 118
 
3.2%
manhattan 106
 
2.8%
east 56
 
1.5%
west 48
 
1.3%
road 27
 
0.7%
island 23
 
0.6%
Other values (1126) 2448
65.4%
2023-12-09T22:06:46.009912image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3305
 
12.1%
1 1627
 
6.0%
0 1609
 
5.9%
4 1220
 
4.5%
7 1173
 
4.3%
3 1169
 
4.3%
e 1032
 
3.8%
t 953
 
3.5%
n 942
 
3.4%
, 884
 
3.2%
Other values (57) 13428
49.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 10919
39.9%
Lowercase Letter 7657
28.0%
Space Separator 3305
 
12.1%
Uppercase Letter 2292
 
8.4%
Other Punctuation 1769
 
6.5%
Dash Punctuation 520
 
1.9%
Close Punctuation 440
 
1.6%
Open Punctuation 440
 
1.6%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N 448
19.5%
Y 442
19.3%
B 310
13.5%
A 225
9.8%
S 213
9.3%
M 125
 
5.5%
E 72
 
3.1%
W 55
 
2.4%
R 51
 
2.2%
P 45
 
2.0%
Other values (15) 306
13.4%
Lowercase Letter
ValueCountFrequency (%)
e 1032
13.5%
t 953
12.4%
n 942
12.3%
a 774
10.1%
r 652
8.5%
o 652
8.5%
l 320
 
4.2%
h 305
 
4.0%
s 296
 
3.9%
u 271
 
3.5%
Other values (14) 1460
19.1%
Decimal Number
ValueCountFrequency (%)
1 1627
14.9%
0 1609
14.7%
4 1220
11.2%
7 1173
10.7%
3 1169
10.7%
8 853
7.8%
2 851
7.8%
9 841
7.7%
6 788
7.2%
5 788
7.2%
Other Punctuation
ValueCountFrequency (%)
, 884
50.0%
. 882
49.9%
? 2
 
0.1%
' 1
 
0.1%
Space Separator
ValueCountFrequency (%)
3305
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 520
100.0%
Close Punctuation
ValueCountFrequency (%)
) 440
100.0%
Open Punctuation
ValueCountFrequency (%)
( 440
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 17393
63.6%
Latin 9949
36.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 1032
 
10.4%
t 953
 
9.6%
n 942
 
9.5%
a 774
 
7.8%
r 652
 
6.6%
o 652
 
6.6%
N 448
 
4.5%
Y 442
 
4.4%
l 320
 
3.2%
B 310
 
3.1%
Other values (39) 3424
34.4%
Common
ValueCountFrequency (%)
3305
19.0%
1 1627
9.4%
0 1609
9.3%
4 1220
 
7.0%
7 1173
 
6.7%
3 1169
 
6.7%
, 884
 
5.1%
. 882
 
5.1%
8 853
 
4.9%
2 851
 
4.9%
Other values (8) 3820
22.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 27342
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3305
 
12.1%
1 1627
 
6.0%
0 1609
 
5.9%
4 1220
 
4.5%
7 1173
 
4.3%
3 1169
 
4.3%
e 1032
 
3.8%
t 953
 
3.5%
n 942
 
3.4%
, 884
 
3.2%
Other values (57) 13428
49.1%

phone_number
Text

Distinct434
Distinct (%)98.6%
Missing0
Missing (%)0.0%
Memory size29.8 KiB
2023-12-09T22:06:46.312318image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters5280
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique431 ?
Unique (%)98.0%

Sample

1st row212-524-4360
2nd row718-946-6812
3rd row718-542-0740
4th row718-230-6250
5th row718-845-1290
ValueCountFrequency (%)
718-381-7100 4
 
0.9%
212-927-1841 3
 
0.7%
718-387-2800 2
 
0.5%
212-831-5153 1
 
0.2%
718-796-8516 1
 
0.2%
212-253-7076 1
 
0.2%
718-545-7095 1
 
0.2%
718-380-6929 1
 
0.2%
718-723-7301 1
 
0.2%
718-861-0521 1
 
0.2%
Other values (424) 424
96.4%
2023-12-09T22:06:46.719346image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 880
16.7%
1 716
13.6%
8 625
11.8%
7 603
11.4%
2 558
10.6%
0 459
8.7%
3 331
 
6.3%
6 301
 
5.7%
4 294
 
5.6%
5 269
 
5.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4400
83.3%
Dash Punctuation 880
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 716
16.3%
8 625
14.2%
7 603
13.7%
2 558
12.7%
0 459
10.4%
3 331
7.5%
6 301
6.8%
4 294
6.7%
5 269
 
6.1%
9 244
 
5.5%
Dash Punctuation
ValueCountFrequency (%)
- 880
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5280
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 880
16.7%
1 716
13.6%
8 625
11.8%
7 603
11.4%
2 558
10.6%
0 459
8.7%
3 331
 
6.3%
6 301
 
5.7%
4 294
 
5.6%
5 269
 
5.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5280
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 880
16.7%
1 716
13.6%
8 625
11.8%
7 603
11.4%
2 558
10.6%
0 459
8.7%
3 331
 
6.3%
6 301
 
5.7%
4 294
 
5.6%
5 269
 
5.1%

fax_number
Text

Distinct437
Distinct (%)99.8%
Missing2
Missing (%)0.5%
Memory size29.7 KiB
2023-12-09T22:06:47.019383image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters5256
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique436 ?
Unique (%)99.5%

Sample

1st row212-524-4365
2nd row718-946-6825
3rd row718-542-0841
4th row718-230-6262
5th row718-843-2072
ValueCountFrequency (%)
212-674-8021 2
 
0.5%
718-403-9553 1
 
0.2%
718-840-1925 1
 
0.2%
718-860-4882 1
 
0.2%
718-843-2072 1
 
0.2%
718-922-2347 1
 
0.2%
718-574-3681 1
 
0.2%
718-596-9434 1
 
0.2%
718-556-4800 1
 
0.2%
718-380-6809 1
 
0.2%
Other values (427) 427
97.5%
2023-12-09T22:06:47.428824image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 876
16.7%
1 694
13.2%
7 642
12.2%
8 627
11.9%
2 583
11.1%
6 342
 
6.5%
3 336
 
6.4%
5 320
 
6.1%
9 302
 
5.7%
4 297
 
5.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4380
83.3%
Dash Punctuation 876
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 694
15.8%
7 642
14.7%
8 627
14.3%
2 583
13.3%
6 342
7.8%
3 336
7.7%
5 320
7.3%
9 302
6.9%
4 297
6.8%
0 237
 
5.4%
Dash Punctuation
ValueCountFrequency (%)
- 876
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5256
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 876
16.7%
1 694
13.2%
7 642
12.2%
8 627
11.9%
2 583
11.1%
6 342
 
6.5%
3 336
 
6.4%
5 320
 
6.1%
9 302
 
5.7%
4 297
 
5.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5256
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 876
16.7%
1 694
13.2%
7 642
12.2%
8 627
11.9%
2 583
11.1%
6 342
 
6.5%
3 336
 
6.4%
5 320
 
6.1%
9 302
 
5.7%
4 297
 
5.7%

school_email
Text

MISSING 

Distinct412
Distinct (%)100.0%
Missing28
Missing (%)6.4%
Memory size33.4 KiB
2023-12-09T22:06:47.756488image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length39
Median length35
Mean length23.65048544
Min length13

Characters and Unicode

Total characters9744
Distinct characters68
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique412 ?
Unique (%)100.0%

Sample

1st rowadmissions@theclintonschool.net
2nd rowscaraway@schools.nyc.gov
3rd rowsburns@schools.nyc.gov
4th rowprandaz@schools.nyc.gov
5th rowinfo@epicschoolsnyc.org
ValueCountFrequency (%)
wmerced2@schools.nyc.gov 1
 
0.2%
jolearchik@schools.nyc.gov 1
 
0.2%
ptate@schools.nyc.gov 1
 
0.2%
foresthillshs.org/apps/contact 1
 
0.2%
mandelaschoolforsocialjustice@gmail.com 1
 
0.2%
info@artsandtech.net 1
 
0.2%
agrafals2@schools.nyc.gov 1
 
0.2%
ms.medina@nycacademy.org 1
 
0.2%
smelo@sljhs.org 1
 
0.2%
or 1
 
0.2%
Other values (407) 407
97.6%
2023-12-09T22:06:48.223470image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o 1274
 
13.1%
s 837
 
8.6%
c 757
 
7.8%
. 678
 
7.0%
n 620
 
6.4%
l 516
 
5.3%
g 474
 
4.9%
h 437
 
4.5%
a 426
 
4.4%
@ 412
 
4.2%
Other values (58) 3313
34.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 8107
83.2%
Other Punctuation 1094
 
11.2%
Decimal Number 304
 
3.1%
Uppercase Letter 226
 
2.3%
Dash Punctuation 7
 
0.1%
Space Separator 5
 
0.1%
Connector Punctuation 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 1274
15.7%
s 837
10.3%
c 757
 
9.3%
n 620
 
7.6%
l 516
 
6.4%
g 474
 
5.8%
h 437
 
5.4%
a 426
 
5.3%
r 369
 
4.6%
e 352
 
4.3%
Other values (16) 2045
25.2%
Uppercase Letter
ValueCountFrequency (%)
M 25
 
11.1%
R 18
 
8.0%
S 18
 
8.0%
K 17
 
7.5%
C 17
 
7.5%
H 13
 
5.8%
D 12
 
5.3%
L 11
 
4.9%
A 11
 
4.9%
Q 9
 
4.0%
Other values (15) 75
33.2%
Decimal Number
ValueCountFrequency (%)
2 72
23.7%
1 41
13.5%
4 40
13.2%
3 37
12.2%
0 28
 
9.2%
7 21
 
6.9%
5 21
 
6.9%
6 16
 
5.3%
8 15
 
4.9%
9 13
 
4.3%
Other Punctuation
ValueCountFrequency (%)
. 678
62.0%
@ 412
37.7%
/ 3
 
0.3%
, 1
 
0.1%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%
Space Separator
ValueCountFrequency (%)
5
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 8333
85.5%
Common 1411
 
14.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 1274
15.3%
s 837
 
10.0%
c 757
 
9.1%
n 620
 
7.4%
l 516
 
6.2%
g 474
 
5.7%
h 437
 
5.2%
a 426
 
5.1%
r 369
 
4.4%
e 352
 
4.2%
Other values (41) 2271
27.3%
Common
ValueCountFrequency (%)
. 678
48.1%
@ 412
29.2%
2 72
 
5.1%
1 41
 
2.9%
4 40
 
2.8%
3 37
 
2.6%
0 28
 
2.0%
7 21
 
1.5%
5 21
 
1.5%
6 16
 
1.1%
Other values (7) 45
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 9744
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o 1274
 
13.1%
s 837
 
8.6%
c 757
 
7.8%
. 678
 
7.0%
n 620
 
6.4%
l 516
 
5.3%
g 474
 
4.9%
h 437
 
4.5%
a 426
 
4.4%
@ 412
 
4.2%
Other values (58) 3313
34.0%

website
Text

Distinct438
Distinct (%)99.5%
Missing0
Missing (%)0.0%
Memory size35.9 KiB
2023-12-09T22:06:48.534671image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length56
Median length36
Mean length26.26363636
Min length9

Characters and Unicode

Total characters11556
Distinct characters65
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique436 ?
Unique (%)99.1%

Sample

1st rowwww.theclintonschool.net
2nd rowschools.nyc.gov/schoolportals/21/K728
3rd rowschools.nyc.gov/SchoolPortals/08/X282
4th rowwww.bkmusicntheatre.com
5th rowwww.epicschoolsnyc.org
ValueCountFrequency (%)
www.epicschoolsnyc.org 2
 
0.5%
www.bard.edu/bhsec 2
 
0.5%
www.fda2.org 1
 
0.2%
www.flushinginternational.org 1
 
0.2%
schools.nyc.gov/schoolportals/17/k524 1
 
0.2%
www.excelsiorprephs.com 1
 
0.2%
www.ichs.weebly.com 1
 
0.2%
www.midwoodhighschool.org 1
 
0.2%
www.ycdhs.org 1
 
0.2%
or 1
 
0.2%
Other values (430) 430
97.3%
2023-12-09T22:06:49.006052image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o 1346
 
11.6%
w 964
 
8.3%
. 912
 
7.9%
s 728
 
6.3%
c 684
 
5.9%
l 634
 
5.5%
h 599
 
5.2%
r 554
 
4.8%
/ 498
 
4.3%
g 438
 
3.8%
Other values (55) 4199
36.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 8940
77.4%
Other Punctuation 1443
 
12.5%
Decimal Number 689
 
6.0%
Uppercase Letter 474
 
4.1%
Dash Punctuation 8
 
0.1%
Space Separator 2
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 1346
15.1%
w 964
10.8%
s 728
 
8.1%
c 684
 
7.7%
l 634
 
7.1%
h 599
 
6.7%
r 554
 
6.2%
g 438
 
4.9%
a 437
 
4.9%
t 437
 
4.9%
Other values (16) 2119
23.7%
Uppercase Letter
ValueCountFrequency (%)
S 141
29.7%
P 121
25.5%
X 44
 
9.3%
K 39
 
8.2%
M 36
 
7.6%
Q 16
 
3.4%
H 15
 
3.2%
A 10
 
2.1%
B 7
 
1.5%
N 5
 
1.1%
Other values (14) 40
 
8.4%
Decimal Number
ValueCountFrequency (%)
2 105
15.2%
0 95
13.8%
1 88
12.8%
4 73
10.6%
3 71
10.3%
5 70
10.2%
9 57
8.3%
6 45
6.5%
7 43
6.2%
8 42
 
6.1%
Other Punctuation
ValueCountFrequency (%)
. 912
63.2%
/ 498
34.5%
: 33
 
2.3%
Dash Punctuation
ValueCountFrequency (%)
- 8
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 9414
81.5%
Common 2142
 
18.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 1346
14.3%
w 964
 
10.2%
s 728
 
7.7%
c 684
 
7.3%
l 634
 
6.7%
h 599
 
6.4%
r 554
 
5.9%
g 438
 
4.7%
a 437
 
4.6%
t 437
 
4.6%
Other values (40) 2593
27.5%
Common
ValueCountFrequency (%)
. 912
42.6%
/ 498
23.2%
2 105
 
4.9%
0 95
 
4.4%
1 88
 
4.1%
4 73
 
3.4%
3 71
 
3.3%
5 70
 
3.3%
9 57
 
2.7%
6 45
 
2.1%
Other values (5) 128
 
6.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11556
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o 1346
 
11.6%
w 964
 
8.3%
. 912
 
7.9%
s 728
 
6.3%
c 684
 
5.9%
l 634
 
5.5%
h 599
 
5.2%
r 554
 
4.8%
/ 498
 
4.3%
g 438
 
3.8%
Other values (55) 4199
36.3%

subway
Text

MISSING 

Distinct196
Distinct (%)54.3%
Missing79
Missing (%)18.0%
Memory size43.9 KiB
2023-12-09T22:06:49.300832image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length194
Median length113
Mean length50.03878116
Min length10

Characters and Unicode

Total characters18064
Distinct characters71
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique126 ?
Unique (%)34.9%

Sample

1st row1, 2, 3, F, M to 14th St - 6th Ave; 4, 5, L, Q to 14th St-Union Square; 6, N, R to 23rd St
2nd rowD, F, N, Q to Coney Island – S llwell Avenue
3rd row2, 3, 4, 5 to Franklin Ave; B, Q to Prospect Park; F to Park Place; S to Botanic Garden
4th row7 to Junction Blvd
5th row4, B, D to 161st St-Yankee Stadium
ValueCountFrequency (%)
to 752
 
16.4%
st 348
 
7.6%
334
 
7.3%
ave 198
 
4.3%
2 129
 
2.8%
5 110
 
2.4%
b 105
 
2.3%
d 89
 
1.9%
a 87
 
1.9%
c 86
 
1.9%
Other values (309) 2350
51.2%
2023-12-09T22:06:49.783036image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4242
23.5%
t 1793
 
9.9%
o 1158
 
6.4%
, 819
 
4.5%
e 814
 
4.5%
r 572
 
3.2%
a 555
 
3.1%
S 555
 
3.1%
n 463
 
2.6%
h 403
 
2.2%
Other values (61) 6690
37.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 8189
45.3%
Space Separator 4242
23.5%
Uppercase Letter 2743
 
15.2%
Decimal Number 1391
 
7.7%
Other Punctuation 1226
 
6.8%
Dash Punctuation 273
 
1.5%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
S 555
20.2%
A 333
12.1%
B 215
 
7.8%
C 213
 
7.8%
F 127
 
4.6%
M 118
 
4.3%
D 117
 
4.3%
R 117
 
4.3%
L 102
 
3.7%
P 100
 
3.6%
Other values (17) 746
27.2%
Lowercase Letter
ValueCountFrequency (%)
t 1793
21.9%
o 1158
14.1%
e 814
9.9%
r 572
 
7.0%
a 555
 
6.8%
n 463
 
5.7%
h 403
 
4.9%
l 345
 
4.2%
d 273
 
3.3%
v 272
 
3.3%
Other values (15) 1541
18.8%
Decimal Number
ValueCountFrequency (%)
1 259
18.6%
2 212
15.2%
5 188
13.5%
4 184
13.2%
3 178
12.8%
6 137
9.8%
7 76
 
5.5%
9 60
 
4.3%
8 51
 
3.7%
0 46
 
3.3%
Other Punctuation
ValueCountFrequency (%)
, 819
66.8%
; 391
31.9%
& 11
 
0.9%
/ 3
 
0.2%
. 1
 
0.1%
' 1
 
0.1%
Dash Punctuation
ValueCountFrequency (%)
- 232
85.0%
– 41
 
15.0%
Space Separator
ValueCountFrequency (%)
4242
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 10932
60.5%
Common 7132
39.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 1793
16.4%
o 1158
 
10.6%
e 814
 
7.4%
r 572
 
5.2%
a 555
 
5.1%
S 555
 
5.1%
n 463
 
4.2%
h 403
 
3.7%
l 345
 
3.2%
A 333
 
3.0%
Other values (42) 3941
36.1%
Common
ValueCountFrequency (%)
4242
59.5%
, 819
 
11.5%
; 391
 
5.5%
1 259
 
3.6%
- 232
 
3.3%
2 212
 
3.0%
5 188
 
2.6%
4 184
 
2.6%
3 178
 
2.5%
6 137
 
1.9%
Other values (9) 290
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 17982
99.5%
Punctuation 41
 
0.2%
None 41
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4242
23.6%
t 1793
 
10.0%
o 1158
 
6.4%
, 819
 
4.6%
e 814
 
4.5%
r 572
 
3.2%
a 555
 
3.1%
S 555
 
3.1%
n 463
 
2.6%
h 403
 
2.2%
Other values (59) 6608
36.7%
Punctuation
ValueCountFrequency (%)
– 41
100.0%
None
ValueCountFrequency (%)
 41
100.0%

bus
Text

Distinct245
Distinct (%)55.8%
Missing1
Missing (%)0.2%
Memory size51.8 KiB
2023-12-09T22:06:50.301065image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length383
Median length141
Mean length63.54897494
Min length8

Characters and Unicode

Total characters27898
Distinct characters22
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique155 ?
Unique (%)35.3%

Sample

1st rowBM1, BM2, BM3, BM4, BxM10, BxM6, BxM7, BxM8, BxM9, M1, M101, M102, M103, M14A, M14D, M15, M15-SBS, M2, M20, M23, M3, M5, M7, M8, QM21, X1, X10, X10B, X12, X14, X17, X2, X27, X28, X37, X38, X42, X5, X63, X64, X68, X7, X9
2nd rowB36, B64, B68, B74, B82, X28, X38
3rd rowBx22, Bx27, Bx36, Bx39, Bx5
4th rowB16, B41, B43, B44-SBS, B45, B48, B49, B69
5th rowQ10, Q37, Q7, Q9, QM18
ValueCountFrequency (%)
m5 60
 
1.1%
x12 55
 
1.0%
x14 53
 
1.0%
bxm4 53
 
1.0%
bx15 51
 
1.0%
m3 50
 
0.9%
bx2 50
 
0.9%
m7 49
 
0.9%
x28 49
 
0.9%
x42 49
 
0.9%
Other values (303) 4844
90.3%
2023-12-09T22:06:51.009802image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
, 4924
17.7%
4924
17.7%
B 2632
9.4%
1 2243
8.0%
M 1814
 
6.5%
2 1368
 
4.9%
x 1347
 
4.8%
4 1212
 
4.3%
3 1000
 
3.6%
Q 966
 
3.5%
Other values (12) 5468
19.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 9529
34.2%
Uppercase Letter 6971
25.0%
Other Punctuation 4924
17.7%
Space Separator 4924
17.7%
Lowercase Letter 1347
 
4.8%
Dash Punctuation 203
 
0.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 2243
23.5%
2 1368
14.4%
4 1212
12.7%
3 1000
10.5%
0 733
 
7.7%
5 731
 
7.7%
6 713
 
7.5%
7 618
 
6.5%
8 543
 
5.7%
9 368
 
3.9%
Uppercase Letter
ValueCountFrequency (%)
B 2632
37.8%
M 1814
26.0%
Q 966
 
13.9%
X 873
 
12.5%
S 505
 
7.2%
A 134
 
1.9%
D 31
 
0.4%
J 16
 
0.2%
Other Punctuation
ValueCountFrequency (%)
, 4924
100.0%
Space Separator
ValueCountFrequency (%)
4924
100.0%
Lowercase Letter
ValueCountFrequency (%)
x 1347
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 203
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 19580
70.2%
Latin 8318
29.8%

Most frequent character per script

Common
ValueCountFrequency (%)
, 4924
25.1%
4924
25.1%
1 2243
11.5%
2 1368
 
7.0%
4 1212
 
6.2%
3 1000
 
5.1%
0 733
 
3.7%
5 731
 
3.7%
6 713
 
3.6%
7 618
 
3.2%
Other values (3) 1114
 
5.7%
Latin
ValueCountFrequency (%)
B 2632
31.6%
M 1814
21.8%
x 1347
16.2%
Q 966
 
11.6%
X 873
 
10.5%
S 505
 
6.1%
A 134
 
1.6%
D 31
 
0.4%
J 16
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 27898
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
, 4924
17.7%
4924
17.7%
B 2632
9.4%
1 2243
8.0%
M 1814
 
6.5%
2 1368
 
4.9%
x 1347
 
4.8%
4 1212
 
4.3%
3 1000
 
3.6%
Q 966
 
3.5%
Other values (12) 5468
19.6%

grades2018
Text

Distinct11
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size26.6 KiB
2023-12-09T22:06:51.191661image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length53
Median length4
Mean length4.686363636
Min length4

Characters and Unicode

Total characters2062
Distinct characters29
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)1.4%

Sample

1st row6-11
2nd rowSchool is structured on credit needs, not grade level
3rd row9-12
4th row9-12
5th row9-12
ValueCountFrequency (%)
9-12 349
71.4%
6-12 76
 
15.5%
credit 6
 
1.2%
level 6
 
1.2%
not 6
 
1.2%
needs 6
 
1.2%
grade 6
 
1.2%
on 6
 
1.2%
structured 6
 
1.2%
is 6
 
1.2%
Other values (8) 16
 
3.3%
2023-12-09T22:06:51.492990image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 437
21.2%
- 435
21.1%
2 430
20.9%
9 349
16.9%
6 80
 
3.9%
50
 
2.4%
e 42
 
2.0%
d 24
 
1.2%
t 24
 
1.2%
r 24
 
1.2%
Other values (19) 167
 
8.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1300
63.0%
Dash Punctuation 435
 
21.1%
Lowercase Letter 258
 
12.5%
Space Separator 50
 
2.4%
Uppercase Letter 12
 
0.6%
Other Punctuation 7
 
0.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 42
16.3%
d 24
9.3%
t 24
9.3%
r 24
9.3%
o 24
9.3%
l 18
7.0%
n 18
7.0%
s 18
7.0%
c 18
7.0%
i 12
 
4.7%
Other values (5) 36
14.0%
Decimal Number
ValueCountFrequency (%)
1 437
33.6%
2 430
33.1%
9 349
26.8%
6 80
 
6.2%
3 1
 
0.1%
8 1
 
0.1%
7 1
 
0.1%
0 1
 
0.1%
Uppercase Letter
ValueCountFrequency (%)
S 6
50.0%
K 4
33.3%
P 2
 
16.7%
Dash Punctuation
ValueCountFrequency (%)
- 435
100.0%
Space Separator
ValueCountFrequency (%)
50
100.0%
Other Punctuation
ValueCountFrequency (%)
, 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1792
86.9%
Latin 270
 
13.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 42
15.6%
d 24
8.9%
t 24
8.9%
r 24
8.9%
o 24
8.9%
l 18
 
6.7%
n 18
 
6.7%
s 18
 
6.7%
c 18
 
6.7%
i 12
 
4.4%
Other values (8) 48
17.8%
Common
ValueCountFrequency (%)
1 437
24.4%
- 435
24.3%
2 430
24.0%
9 349
19.5%
6 80
 
4.5%
50
 
2.8%
, 7
 
0.4%
3 1
 
0.1%
8 1
 
0.1%
7 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2062
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 437
21.2%
- 435
21.1%
2 430
20.9%
9 349
16.9%
6 80
 
3.9%
50
 
2.4%
e 42
 
2.0%
d 24
 
1.2%
t 24
 
1.2%
r 24
 
1.2%
Other values (19) 167
 
8.1%

finalgrades
Text

Distinct8
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size26.6 KiB
2023-12-09T22:06:51.673427image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length53
Median length4
Mean length4.672727273
Min length4

Characters and Unicode

Total characters2056
Distinct characters28
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)0.5%

Sample

1st row6-12
2nd rowSchool is structured on credit needs, not grade level
3rd row9-12
4th row9-12
5th row9-12
ValueCountFrequency (%)
9-12 342
70.1%
6-12 79
 
16.2%
9-14 7
 
1.4%
school 6
 
1.2%
is 6
 
1.2%
structured 6
 
1.2%
on 6
 
1.2%
credit 6
 
1.2%
needs 6
 
1.2%
not 6
 
1.2%
Other values (6) 18
 
3.7%
2023-12-09T22:06:51.957768image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 434
21.1%
- 434
21.1%
2 427
20.8%
9 349
17.0%
6 79
 
3.8%
48
 
2.3%
e 42
 
2.0%
d 24
 
1.2%
r 24
 
1.2%
t 24
 
1.2%
Other values (18) 171
 
8.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1298
63.1%
Dash Punctuation 434
 
21.1%
Lowercase Letter 258
 
12.5%
Space Separator 48
 
2.3%
Uppercase Letter 12
 
0.6%
Other Punctuation 6
 
0.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 42
16.3%
d 24
9.3%
r 24
9.3%
t 24
9.3%
o 24
9.3%
l 18
7.0%
c 18
7.0%
n 18
7.0%
s 18
7.0%
u 12
 
4.7%
Other values (5) 36
14.0%
Decimal Number
ValueCountFrequency (%)
1 434
33.4%
2 427
32.9%
9 349
26.9%
6 79
 
6.1%
4 7
 
0.5%
8 1
 
0.1%
7 1
 
0.1%
Uppercase Letter
ValueCountFrequency (%)
S 6
50.0%
K 4
33.3%
P 2
 
16.7%
Dash Punctuation
ValueCountFrequency (%)
- 434
100.0%
Space Separator
ValueCountFrequency (%)
48
100.0%
Other Punctuation
ValueCountFrequency (%)
, 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1786
86.9%
Latin 270
 
13.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 42
15.6%
d 24
8.9%
r 24
8.9%
t 24
8.9%
o 24
8.9%
l 18
 
6.7%
c 18
 
6.7%
n 18
 
6.7%
s 18
 
6.7%
u 12
 
4.4%
Other values (8) 48
17.8%
Common
ValueCountFrequency (%)
1 434
24.3%
- 434
24.3%
2 427
23.9%
9 349
19.5%
6 79
 
4.4%
48
 
2.7%
4 7
 
0.4%
, 6
 
0.3%
8 1
 
0.1%
7 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2056
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 434
21.1%
- 434
21.1%
2 427
20.8%
9 349
17.0%
6 79
 
3.8%
48
 
2.3%
e 42
 
2.0%
d 24
 
1.2%
r 24
 
1.2%
t 24
 
1.2%
Other values (18) 171
 
8.3%

total_students
Text

Distinct344
Distinct (%)78.2%
Missing0
Missing (%)0.0%
Memory size26.0 KiB
2023-12-09T22:06:52.516506image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length4
Median length3
Mean length3.134090909
Min length2

Characters and Unicode

Total characters1379
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique267 ?
Unique (%)60.7%

Sample

1st row376
2nd row206
3rd row338
4th row352
5th row175
ValueCountFrequency (%)
232 4
 
0.9%
333 4
 
0.9%
410 4
 
0.9%
457 3
 
0.7%
423 3
 
0.7%
353 3
 
0.7%
427 3
 
0.7%
451 3
 
0.7%
293 3
 
0.7%
443 3
 
0.7%
Other values (334) 407
92.5%
2023-12-09T22:06:53.283180image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 204
14.8%
4 190
13.8%
2 162
11.7%
5 158
11.5%
1 139
10.1%
6 120
8.7%
0 114
8.3%
7 108
7.8%
9 105
7.6%
8 79
 
5.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1379
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 204
14.8%
4 190
13.8%
2 162
11.7%
5 158
11.5%
1 139
10.1%
6 120
8.7%
0 114
8.3%
7 108
7.8%
9 105
7.6%
8 79
 
5.7%

Most occurring scripts

ValueCountFrequency (%)
Common 1379
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 204
14.8%
4 190
13.8%
2 162
11.7%
5 158
11.5%
1 139
10.1%
6 120
8.7%
0 114
8.3%
7 108
7.8%
9 105
7.6%
8 79
 
5.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1379
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 204
14.8%
4 190
13.8%
2 162
11.7%
5 158
11.5%
1 139
10.1%
6 120
8.7%
0 114
8.3%
7 108
7.8%
9 105
7.6%
8 79
 
5.7%

start_time
Text

MISSING 

Distinct47
Distinct (%)10.9%
Missing9
Missing (%)2.0%
Memory size26.5 KiB
2023-12-09T22:06:53.536183image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length6
Median length6
Mean length4.893271462
Min length3

Characters and Unicode

Total characters2109
Distinct characters13
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique25 ?
Unique (%)5.8%

Sample

1st row8:20am
2nd row8:10am
3rd row9am
4th row8am
5th row8:30am
ValueCountFrequency (%)
8am 139
32.3%
8:30am 65
15.1%
8:15am 44
 
10.2%
8:45am 31
 
7.2%
8:20am 27
 
6.3%
9am 20
 
4.6%
8:10am 13
 
3.0%
7:45am 8
 
1.9%
8:40am 8
 
1.9%
8:25am 8
 
1.9%
Other values (37) 68
15.8%
2023-12-09T22:06:53.923823image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
m 431
20.4%
a 429
20.3%
8 377
17.9%
: 272
12.9%
0 146
 
6.9%
5 130
 
6.2%
3 86
 
4.1%
1 70
 
3.3%
4 54
 
2.6%
2 50
 
2.4%
Other values (3) 64
 
3.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 975
46.2%
Lowercase Letter 862
40.9%
Other Punctuation 272
 
12.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
8 377
38.7%
0 146
 
15.0%
5 130
 
13.3%
3 86
 
8.8%
1 70
 
7.2%
4 54
 
5.5%
2 50
 
5.1%
9 34
 
3.5%
7 28
 
2.9%
Lowercase Letter
ValueCountFrequency (%)
m 431
50.0%
a 429
49.8%
p 2
 
0.2%
Other Punctuation
ValueCountFrequency (%)
: 272
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1247
59.1%
Latin 862
40.9%

Most frequent character per script

Common
ValueCountFrequency (%)
8 377
30.2%
: 272
21.8%
0 146
 
11.7%
5 130
 
10.4%
3 86
 
6.9%
1 70
 
5.6%
4 54
 
4.3%
2 50
 
4.0%
9 34
 
2.7%
7 28
 
2.2%
Latin
ValueCountFrequency (%)
m 431
50.0%
a 429
49.8%
p 2
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2109
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
m 431
20.4%
a 429
20.3%
8 377
17.9%
: 272
12.9%
0 146
 
6.9%
5 130
 
6.2%
3 86
 
4.1%
1 70
 
3.3%
4 54
 
2.6%
2 50
 
2.4%
Other values (3) 64
 
3.0%

end_time
Text

MISSING 

Distinct69
Distinct (%)16.0%
Missing9
Missing (%)2.0%
Memory size26.7 KiB
2023-12-09T22:06:54.266908image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length6
Median length6
Mean length5.457076566
Min length3

Characters and Unicode

Total characters2352
Distinct characters13
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique36 ?
Unique (%)8.4%

Sample

1st row2:45pm
2nd row3pm
3rd row4pm
4th row3:10pm
5th row3:20pm
ValueCountFrequency (%)
3pm 54
 
12.5%
3:30pm 49
 
11.4%
3:45pm 28
 
6.5%
3:15pm 27
 
6.3%
2:20pm 23
 
5.3%
4pm 23
 
5.3%
2:40pm 22
 
5.1%
2:45pm 21
 
4.9%
2:30pm 20
 
4.6%
3:20pm 16
 
3.7%
Other values (59) 148
34.3%
2023-12-09T22:06:54.707723image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
p 431
18.3%
m 431
18.3%
3 373
15.9%
: 353
15.0%
0 194
8.2%
2 188
8.0%
5 158
 
6.7%
4 131
 
5.6%
1 58
 
2.5%
7 12
 
0.5%
Other values (3) 23
 
1.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1137
48.3%
Lowercase Letter 862
36.6%
Other Punctuation 353
 
15.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 373
32.8%
0 194
17.1%
2 188
16.5%
5 158
13.9%
4 131
 
11.5%
1 58
 
5.1%
7 12
 
1.1%
6 9
 
0.8%
8 9
 
0.8%
9 5
 
0.4%
Lowercase Letter
ValueCountFrequency (%)
p 431
50.0%
m 431
50.0%
Other Punctuation
ValueCountFrequency (%)
: 353
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1490
63.4%
Latin 862
36.6%

Most frequent character per script

Common
ValueCountFrequency (%)
3 373
25.0%
: 353
23.7%
0 194
13.0%
2 188
12.6%
5 158
10.6%
4 131
 
8.8%
1 58
 
3.9%
7 12
 
0.8%
6 9
 
0.6%
8 9
 
0.6%
Latin
ValueCountFrequency (%)
p 431
50.0%
m 431
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2352
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
p 431
18.3%
m 431
18.3%
3 373
15.9%
: 353
15.0%
0 194
8.2%
2 188
8.0%
5 158
 
6.7%
4 131
 
5.6%
1 58
 
2.5%
7 12
 
0.5%
Other values (3) 23
 
1.0%

addtl_info1
Text

MISSING 

Distinct177
Distinct (%)59.4%
Missing142
Missing (%)32.3%
Memory size41.1 KiB
2023-12-09T22:06:54.959532image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length437
Median length199
Mean length68.60067114
Min length7

Characters and Unicode

Total characters20443
Distinct characters51
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique150 ?
Unique (%)50.3%

Sample

1st rowThe Learning to Work (LTW) program assists students in overcoming obstacles that impede their progress toward a high school diploma. LTW offers academic and student support, career and educational exploration, work preparation, skills development, and internships that prepare students for rewarding employment and educational experiences after graduation. These LTW supports are provided by a community-based organization (CBO) partner.
2nd rowCommunity Service Expected; Online Grading System; Saturday Programs; Student/Parent Orientation; Uniform
3rd rowInternships
4th rowCommunity Service Expected; Uniform
5th rowCommunity School
ValueCountFrequency (%)
program 179
 
7.6%
community 161
 
6.9%
internships 160
 
6.8%
uniform 139
 
5.9%
extended 131
 
5.6%
summer 130
 
5.5%
day 128
 
5.4%
expected 117
 
5.0%
orientation 111
 
4.7%
programs 105
 
4.5%
Other values (81) 988
42.1%
2023-12-09T22:06:55.380512image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2051
 
10.0%
e 1813
 
8.9%
r 1696
 
8.3%
n 1424
 
7.0%
t 1285
 
6.3%
i 1157
 
5.7%
m 1083
 
5.3%
o 1053
 
5.2%
a 913
 
4.5%
; 745
 
3.6%
Other values (41) 7223
35.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 15190
74.3%
Uppercase Letter 2278
 
11.1%
Space Separator 2051
 
10.0%
Other Punctuation 808
 
4.0%
Close Punctuation 50
 
0.2%
Open Punctuation 50
 
0.2%
Dash Punctuation 16
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 1813
11.9%
r 1696
11.2%
n 1424
9.4%
t 1285
 
8.5%
i 1157
 
7.6%
m 1083
 
7.1%
o 1053
 
6.9%
a 913
 
6.0%
d 694
 
4.6%
s 660
 
4.3%
Other values (14) 3412
22.5%
Uppercase Letter
ValueCountFrequency (%)
S 499
21.9%
P 323
14.2%
C 276
12.1%
E 249
10.9%
I 176
 
7.7%
O 166
 
7.3%
U 139
 
6.1%
D 129
 
5.7%
T 112
 
4.9%
G 53
 
2.3%
Other values (9) 156
 
6.8%
Other Punctuation
ValueCountFrequency (%)
; 745
92.2%
/ 42
 
5.2%
, 12
 
1.5%
. 9
 
1.1%
Space Separator
ValueCountFrequency (%)
2051
100.0%
Close Punctuation
ValueCountFrequency (%)
) 50
100.0%
Open Punctuation
ValueCountFrequency (%)
( 50
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 16
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 17468
85.4%
Common 2975
 
14.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 1813
 
10.4%
r 1696
 
9.7%
n 1424
 
8.2%
t 1285
 
7.4%
i 1157
 
6.6%
m 1083
 
6.2%
o 1053
 
6.0%
a 913
 
5.2%
d 694
 
4.0%
s 660
 
3.8%
Other values (33) 5690
32.6%
Common
ValueCountFrequency (%)
2051
68.9%
; 745
 
25.0%
) 50
 
1.7%
( 50
 
1.7%
/ 42
 
1.4%
- 16
 
0.5%
, 12
 
0.4%
. 9
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 20443
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2051
 
10.0%
e 1813
 
8.9%
r 1696
 
8.3%
n 1424
 
7.0%
t 1285
 
6.3%
i 1157
 
5.7%
m 1083
 
5.3%
o 1053
 
5.2%
a 913
 
4.5%
; 745
 
3.6%
Other values (41) 7223
35.3%

extracurricular_activities
Text

Distinct436
Distinct (%)99.8%
Missing3
Missing (%)0.7%
Memory size171.5 KiB
2023-12-09T22:06:55.762112image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length504
Median length371
Mean length292.1922197
Min length25

Characters and Unicode

Total characters127688
Distinct characters84
Distinct categories11 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique435 ?
Unique (%)99.5%

Sample

1st rowCUNY College Now, Technology, Model UN, Student Government, School Leadership Team, Music, School Musical, National Honor Society, The Clinton Post (School Newspaper), Clinton Soup (Literary Magazine), GLSEN, Glee
2nd rowAdvisory Leadership, Student Council, Community Service Leadership, School Leadership Team, A er-School Enrichment, Peer Tutoring, School Newspaper
3rd rowAcademy of Health, Advisory, Annual Breast Cancer Walk, Purses for Life, Ambassadors, Conflict Resolution Program-Effective Alternatives in Reconciliation Services (EARS), Peer Tutoring, Student Government, Step Team, Cheerleading, Big Sister/Little Sister Program, Chorus
4th rowChess, The Step Team, Fashion, Tech Team, WomenÂ’s Group; Extensive arts after-school program: Tech, Dance, Drama, and Chorus Companies; Crew program that trains students in running the lights, sound, video, and all backstage and pit crew responsibilities; Saturday and after-school classes for Regents Preparation; School Leadership Team; Student Government; At least three annual major school-wide productions; Two annual talent shows
5th rowBased on student interest
ValueCountFrequency (%)
student 464
 
2.9%
club 397
 
2.4%
and 383
 
2.4%
dance 272
 
1.7%
government 244
 
1.5%
society 226
 
1.4%
team 223
 
1.4%
yearbook 217
 
1.3%
tutoring 210
 
1.3%
peer 207
 
1.3%
Other values (2437) 13387
82.5%
2023-12-09T22:06:56.323482image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
15799
 
12.4%
e 10415
 
8.2%
o 7677
 
6.0%
a 7359
 
5.8%
r 7248
 
5.7%
n 7245
 
5.7%
t 7224
 
5.7%
, 7137
 
5.6%
i 7002
 
5.5%
s 4475
 
3.5%
Other values (74) 46107
36.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 86596
67.8%
Uppercase Letter 16797
 
13.2%
Space Separator 15799
 
12.4%
Other Punctuation 7681
 
6.0%
Dash Punctuation 306
 
0.2%
Close Punctuation 186
 
0.1%
Open Punctuation 186
 
0.1%
Final Punctuation 68
 
0.1%
Decimal Number 62
 
< 0.1%
Initial Punctuation 4
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
S 2476
14.7%
C 2055
12.2%
A 1450
 
8.6%
P 1194
 
7.1%
T 1179
 
7.0%
M 1087
 
6.5%
D 885
 
5.3%
G 802
 
4.8%
H 584
 
3.5%
N 582
 
3.5%
Other values (17) 4503
26.8%
Lowercase Letter
ValueCountFrequency (%)
e 10415
12.0%
o 7677
 
8.9%
a 7359
 
8.5%
r 7248
 
8.4%
n 7245
 
8.4%
t 7224
 
8.3%
i 7002
 
8.1%
s 4475
 
5.2%
l 3949
 
4.6%
u 3527
 
4.1%
Other values (16) 20475
23.6%
Other Punctuation
ValueCountFrequency (%)
, 7137
92.9%
/ 170
 
2.2%
; 106
 
1.4%
. 90
 
1.2%
& 68
 
0.9%
' 45
 
0.6%
: 43
 
0.6%
! 19
 
0.2%
? 2
 
< 0.1%
¡ 1
 
< 0.1%
Decimal Number
ValueCountFrequency (%)
2 15
24.2%
0 14
22.6%
1 9
14.5%
3 8
12.9%
4 6
 
9.7%
5 4
 
6.5%
9 3
 
4.8%
6 1
 
1.6%
8 1
 
1.6%
7 1
 
1.6%
Dash Punctuation
ValueCountFrequency (%)
- 301
98.4%
– 3
 
1.0%
— 2
 
0.7%
Final Punctuation
ValueCountFrequency (%)
’ 67
98.5%
” 1
 
1.5%
Initial Punctuation
ValueCountFrequency (%)
‘ 3
75.0%
“ 1
 
25.0%
Space Separator
ValueCountFrequency (%)
15799
100.0%
Close Punctuation
ValueCountFrequency (%)
) 186
100.0%
Open Punctuation
ValueCountFrequency (%)
( 186
100.0%
Math Symbol
ValueCountFrequency (%)
+ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 103393
81.0%
Common 24295
 
19.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 10415
 
10.1%
o 7677
 
7.4%
a 7359
 
7.1%
r 7248
 
7.0%
n 7245
 
7.0%
t 7224
 
7.0%
i 7002
 
6.8%
s 4475
 
4.3%
l 3949
 
3.8%
u 3527
 
3.4%
Other values (43) 37272
36.0%
Common
ValueCountFrequency (%)
15799
65.0%
, 7137
29.4%
- 301
 
1.2%
) 186
 
0.8%
( 186
 
0.8%
/ 170
 
0.7%
; 106
 
0.4%
. 90
 
0.4%
& 68
 
0.3%
’ 67
 
0.3%
Other values (21) 185
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 127532
99.9%
None 79
 
0.1%
Punctuation 77
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
15799
 
12.4%
e 10415
 
8.2%
o 7677
 
6.0%
a 7359
 
5.8%
r 7248
 
5.7%
n 7245
 
5.7%
t 7224
 
5.7%
, 7137
 
5.6%
i 7002
 
5.5%
s 4475
 
3.5%
Other values (66) 45951
36.0%
None
ValueCountFrequency (%)
 78
98.7%
¡ 1
 
1.3%
Punctuation
ValueCountFrequency (%)
’ 67
87.0%
‘ 3
 
3.9%
– 3
 
3.9%
— 2
 
2.6%
“ 1
 
1.3%
” 1
 
1.3%

psal_sports_boys
Text

MISSING 

Distinct159
Distinct (%)38.6%
Missing28
Missing (%)6.4%
Memory size51.1 KiB
2023-12-09T22:06:56.546225image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length198
Median length113.5
Mean length67.57524272
Min length6

Characters and Unicode

Total characters27841
Distinct characters33
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique82 ?
Unique (%)19.9%

Sample

1st rowBaseball, Basketball, Cross Country, Fencing
2nd rowBaseball, Basketball, Cross Country, Indoor Track, Outdoor Track, Soccer, Swimming
3rd rowBaseball, Basketball, Football, Indoor Track, Outdoor Track, Soccer, Wrestling
4th rowBaseball, Basketball, Bowling, Football, Indoor Track, Outdoor Track, Soccer, Volleyball, Wrestling
5th rowBaseball, Basketball, Bowling, Cross Country, Outdoor Track, Soccer, Tennis, Volleyball, Wrestling
ValueCountFrequency (%)
basketball 391
12.6%
track 336
10.8%
baseball 328
10.6%
soccer 311
10.0%
volleyball 205
 
6.6%
outdoor 187
 
6.0%
bowling 173
 
5.6%
wrestling 162
 
5.2%
indoor 149
 
4.8%
cross 140
 
4.5%
Other values (13) 716
23.1%
2023-12-09T22:06:57.394074image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
l 3082
 
11.1%
2686
 
9.6%
a 2417
 
8.7%
, 2192
 
7.9%
o 1975
 
7.1%
e 1601
 
5.8%
r 1465
 
5.3%
s 1384
 
5.0%
b 1198
 
4.3%
n 1169
 
4.2%
Other values (23) 8672
31.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 19865
71.4%
Uppercase Letter 3098
 
11.1%
Space Separator 2686
 
9.6%
Other Punctuation 2192
 
7.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
l 3082
15.5%
a 2417
12.2%
o 1975
9.9%
e 1601
8.1%
r 1465
7.4%
s 1384
 
7.0%
b 1198
 
6.0%
n 1169
 
5.9%
t 1057
 
5.3%
c 1042
 
5.2%
Other values (8) 3475
17.5%
Uppercase Letter
ValueCountFrequency (%)
B 922
29.8%
T 470
15.2%
S 380
12.3%
C 280
 
9.0%
V 205
 
6.6%
O 187
 
6.0%
F 165
 
5.3%
W 162
 
5.2%
I 150
 
4.8%
H 103
 
3.3%
Other values (3) 74
 
2.4%
Space Separator
ValueCountFrequency (%)
2686
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2192
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 22963
82.5%
Common 4878
 
17.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
l 3082
13.4%
a 2417
 
10.5%
o 1975
 
8.6%
e 1601
 
7.0%
r 1465
 
6.4%
s 1384
 
6.0%
b 1198
 
5.2%
n 1169
 
5.1%
t 1057
 
4.6%
c 1042
 
4.5%
Other values (21) 6573
28.6%
Common
ValueCountFrequency (%)
2686
55.1%
, 2192
44.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 27841
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
l 3082
 
11.1%
2686
 
9.6%
a 2417
 
8.7%
, 2192
 
7.9%
o 1975
 
7.1%
e 1601
 
5.8%
r 1465
 
5.3%
s 1384
 
5.0%
b 1198
 
4.3%
n 1169
 
4.2%
Other values (23) 8672
31.1%

psal_sports_girls
Text

MISSING 

Distinct174
Distinct (%)43.0%
Missing35
Missing (%)8.0%
Memory size51.6 KiB
2023-12-09T22:06:57.680760image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length209
Median length135
Mean length70.43209877
Min length10

Characters and Unicode

Total characters28525
Distinct characters34
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique93 ?
Unique (%)23.0%

Sample

1st rowBasketball, Cross Country, Indoor Track, Outdoor Track, Softball, Volleyball
2nd rowBasketball, Soccer
3rd rowBasketball, Flag Football, Indoor Track, Soccer, Softball, Tennis, Volleyball
4th rowBasketball, Bowling, Cross Country, Flag Football, Handball, Indoor Track, Outdoor Track, Softball, Volleyball
5th rowBasketball, Cross Country, Handball, Indoor Track, Outdoor Track, Soccer, Softball, Tennis, Volleyball
ValueCountFrequency (%)
basketball 359
11.1%
track 343
10.6%
volleyball 342
10.5%
softball 309
 
9.5%
soccer 215
 
6.6%
tennis 200
 
6.2%
outdoor 178
 
5.5%
indoor 165
 
5.1%
country 151
 
4.7%
cross 151
 
4.7%
Other values (13) 833
25.7%
2023-12-09T22:06:58.169000image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
l 3506
 
12.3%
2841
 
10.0%
o 2376
 
8.3%
a 2298
 
8.1%
, 2163
 
7.6%
b 1287
 
4.5%
r 1287
 
4.5%
e 1279
 
4.5%
t 1263
 
4.4%
n 1226
 
4.3%
Other values (24) 8999
31.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 20275
71.1%
Uppercase Letter 3246
 
11.4%
Space Separator 2841
 
10.0%
Other Punctuation 2163
 
7.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
l 3506
17.3%
o 2376
11.7%
a 2298
11.3%
b 1287
 
6.3%
r 1287
 
6.3%
e 1279
 
6.3%
t 1263
 
6.2%
n 1226
 
6.0%
s 1040
 
5.1%
c 864
 
4.3%
Other values (9) 3849
19.0%
Uppercase Letter
ValueCountFrequency (%)
T 597
18.4%
S 587
18.1%
B 547
16.9%
V 342
10.5%
C 302
9.3%
F 285
8.8%
O 178
 
5.5%
I 165
 
5.1%
H 73
 
2.2%
G 66
 
2.0%
Other values (3) 104
 
3.2%
Space Separator
ValueCountFrequency (%)
2841
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2163
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 23521
82.5%
Common 5004
 
17.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
l 3506
14.9%
o 2376
 
10.1%
a 2298
 
9.8%
b 1287
 
5.5%
r 1287
 
5.5%
e 1279
 
5.4%
t 1263
 
5.4%
n 1226
 
5.2%
s 1040
 
4.4%
c 864
 
3.7%
Other values (22) 7095
30.2%
Common
ValueCountFrequency (%)
2841
56.8%
, 2163
43.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 28525
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
l 3506
 
12.3%
2841
 
10.0%
o 2376
 
8.3%
a 2298
 
8.1%
, 2163
 
7.6%
b 1287
 
4.5%
r 1287
 
4.5%
e 1279
 
4.5%
t 1263
 
4.4%
n 1226
 
4.3%
Other values (24) 8999
31.5%

psal_sports_coed
Text

MISSING 

Distinct17
Distinct (%)9.6%
Missing262
Missing (%)59.5%
Memory size20.0 KiB
2023-12-09T22:06:58.367340image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length34
Median length21.5
Mean length10.31460674
Min length4

Characters and Unicode

Total characters1836
Distinct characters26
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)2.8%

Sample

1st rowStunt
2nd rowCricket, Double Dutch
3rd rowCricket, Stunt
4th rowCricket
5th rowCricket, Golf
ValueCountFrequency (%)
stunt 71
23.5%
cricket 66
21.9%
golf 62
20.5%
double 45
14.9%
dutch 45
14.9%
outdoor 4
 
1.3%
track 4
 
1.3%
table 2
 
0.7%
tennis 2
 
0.7%
wrestling 1
 
0.3%
2023-12-09T22:06:58.696774image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
t 258
14.1%
u 165
 
9.0%
124
 
6.8%
e 116
 
6.3%
o 115
 
6.3%
c 115
 
6.3%
l 110
 
6.0%
D 90
 
4.9%
n 76
 
4.1%
r 75
 
4.1%
Other values (16) 592
32.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1337
72.8%
Uppercase Letter 302
 
16.4%
Space Separator 124
 
6.8%
Other Punctuation 73
 
4.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 258
19.3%
u 165
12.3%
e 116
8.7%
o 115
8.6%
c 115
8.6%
l 110
8.2%
n 76
 
5.7%
r 75
 
5.6%
k 70
 
5.2%
i 69
 
5.2%
Other values (7) 168
12.6%
Uppercase Letter
ValueCountFrequency (%)
D 90
29.8%
S 71
23.5%
C 66
21.9%
G 62
20.5%
T 8
 
2.6%
O 4
 
1.3%
W 1
 
0.3%
Space Separator
ValueCountFrequency (%)
124
100.0%
Other Punctuation
ValueCountFrequency (%)
, 73
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1639
89.3%
Common 197
 
10.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 258
15.7%
u 165
 
10.1%
e 116
 
7.1%
o 115
 
7.0%
c 115
 
7.0%
l 110
 
6.7%
D 90
 
5.5%
n 76
 
4.6%
r 75
 
4.6%
S 71
 
4.3%
Other values (14) 448
27.3%
Common
ValueCountFrequency (%)
124
62.9%
, 73
37.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1836
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t 258
14.1%
u 165
 
9.0%
124
 
6.8%
e 116
 
6.3%
o 115
 
6.3%
c 115
 
6.3%
l 110
 
6.0%
D 90
 
4.9%
n 76
 
4.1%
r 75
 
4.1%
Other values (16) 592
32.2%

school_sports
Text

MISSING 

Distinct279
Distinct (%)92.4%
Missing138
Missing (%)31.4%
Memory size40.0 KiB
2023-12-09T22:06:59.077793image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length481
Median length118.5
Mean length62.37748344
Min length6

Characters and Unicode

Total characters18838
Distinct characters76
Distinct categories10 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique271 ?
Unique (%)89.7%

Sample

1st rowCross Country, Track and Field, Soccer, Flag Football, Basketball
2nd rowBasketball
3rd rowCheerleading
4th rowBadminton, Baseball, Fitness, Football, Soccer, Yoga, Volleyball, Basketball
5th rowCheerleading, Fencing
ValueCountFrequency (%)
basketball 161
 
6.7%
soccer 94
 
3.9%
volleyball 87
 
3.6%
cheerleading 75
 
3.1%
boys 70
 
2.9%
football 70
 
2.9%
girls 68
 
2.8%
intramural 67
 
2.8%
and 63
 
2.6%
track 63
 
2.6%
Other values (403) 1580
65.9%
2023-12-09T22:06:59.630419image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2097
 
11.1%
l 1676
 
8.9%
a 1562
 
8.3%
e 1367
 
7.3%
o 998
 
5.3%
t 956
 
5.1%
r 881
 
4.7%
s 847
 
4.5%
n 842
 
4.5%
, 793
 
4.2%
Other values (66) 6819
36.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 13562
72.0%
Uppercase Letter 2119
 
11.2%
Space Separator 2097
 
11.1%
Other Punctuation 922
 
4.9%
Dash Punctuation 61
 
0.3%
Decimal Number 26
 
0.1%
Close Punctuation 24
 
0.1%
Open Punctuation 24
 
0.1%
Final Punctuation 2
 
< 0.1%
Initial Punctuation 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
l 1676
12.4%
a 1562
11.5%
e 1367
10.1%
o 998
 
7.4%
t 956
 
7.0%
r 881
 
6.5%
s 847
 
6.2%
n 842
 
6.2%
i 792
 
5.8%
b 563
 
4.2%
Other values (16) 3078
22.7%
Uppercase Letter
ValueCountFrequency (%)
B 334
15.8%
S 321
15.1%
C 220
10.4%
F 203
9.6%
T 196
9.2%
V 123
 
5.8%
G 93
 
4.4%
I 84
 
4.0%
A 75
 
3.5%
W 62
 
2.9%
Other values (16) 408
19.3%
Decimal Number
ValueCountFrequency (%)
1 5
19.2%
3 4
15.4%
2 4
15.4%
9 3
11.5%
7 3
11.5%
0 3
11.5%
8 2
 
7.7%
4 1
 
3.8%
5 1
 
3.8%
Other Punctuation
ValueCountFrequency (%)
, 793
86.0%
. 45
 
4.9%
: 36
 
3.9%
; 25
 
2.7%
& 13
 
1.4%
/ 5
 
0.5%
' 3
 
0.3%
! 2
 
0.2%
Final Punctuation
ValueCountFrequency (%)
” 1
50.0%
’ 1
50.0%
Space Separator
ValueCountFrequency (%)
2097
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 61
100.0%
Close Punctuation
ValueCountFrequency (%)
) 24
100.0%
Open Punctuation
ValueCountFrequency (%)
( 24
100.0%
Initial Punctuation
ValueCountFrequency (%)
“ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 15681
83.2%
Common 3157
 
16.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
l 1676
 
10.7%
a 1562
 
10.0%
e 1367
 
8.7%
o 998
 
6.4%
t 956
 
6.1%
r 881
 
5.6%
s 847
 
5.4%
n 842
 
5.4%
i 792
 
5.1%
b 563
 
3.6%
Other values (42) 5197
33.1%
Common
ValueCountFrequency (%)
2097
66.4%
, 793
 
25.1%
- 61
 
1.9%
. 45
 
1.4%
: 36
 
1.1%
; 25
 
0.8%
) 24
 
0.8%
( 24
 
0.8%
& 13
 
0.4%
/ 5
 
0.2%
Other values (14) 34
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 18832
> 99.9%
None 3
 
< 0.1%
Punctuation 3
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2097
 
11.1%
l 1676
 
8.9%
a 1562
 
8.3%
e 1367
 
7.3%
o 998
 
5.3%
t 956
 
5.1%
r 881
 
4.7%
s 847
 
4.5%
n 842
 
4.5%
, 793
 
4.2%
Other values (62) 6813
36.2%
None
ValueCountFrequency (%)
 3
100.0%
Punctuation
ValueCountFrequency (%)
“ 1
33.3%
” 1
33.3%
’ 1
33.3%

graduation_rate
Text

MISSING 

Distinct270
Distinct (%)70.5%
Missing57
Missing (%)13.0%
Memory size27.1 KiB
2023-12-09T22:06:59.908487image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length11
Median length11
Mean length10.48302872
Min length1

Characters and Unicode

Total characters4015
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique189 ?
Unique (%)49.3%

Sample

1st row0.612999976
2nd row0.833000004
3rd row0.755999982
4th row0.683000028
5th row0.758000016
ValueCountFrequency (%)
1 8
 
2.1%
0.978999972 6
 
1.6%
0.755999982 5
 
1.3%
0.702000022 4
 
1.0%
0.726999998 4
 
1.0%
0.973999977 4
 
1.0%
0.648000002 4
 
1.0%
0.943000019 3
 
0.8%
0.816999972 3
 
0.8%
0.878000021 3
 
0.8%
Other values (260) 339
88.5%
2023-12-09T22:07:00.322902image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1193
29.7%
9 990
24.7%
. 375
 
9.3%
7 264
 
6.6%
8 257
 
6.4%
2 199
 
5.0%
6 178
 
4.4%
1 168
 
4.2%
5 149
 
3.7%
4 131
 
3.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3640
90.7%
Other Punctuation 375
 
9.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1193
32.8%
9 990
27.2%
7 264
 
7.3%
8 257
 
7.1%
2 199
 
5.5%
6 178
 
4.9%
1 168
 
4.6%
5 149
 
4.1%
4 131
 
3.6%
3 111
 
3.0%
Other Punctuation
ValueCountFrequency (%)
. 375
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4015
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1193
29.7%
9 990
24.7%
. 375
 
9.3%
7 264
 
6.6%
8 257
 
6.4%
2 199
 
5.0%
6 178
 
4.4%
1 168
 
4.2%
5 149
 
3.7%
4 131
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4015
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1193
29.7%
9 990
24.7%
. 375
 
9.3%
7 264
 
6.6%
8 257
 
6.4%
2 199
 
5.0%
6 178
 
4.4%
1 168
 
4.2%
5 149
 
3.7%
4 131
 
3.3%

attendance_rate
Text

Distinct34
Distinct (%)7.7%
Missing0
Missing (%)0.0%
Memory size29.3 KiB
2023-12-09T22:07:00.562762image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length11
Median length11
Mean length10.94772727
Min length4

Characters and Unicode

Total characters4817
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7 ?
Unique (%)1.6%

Sample

1st row0.970000029
2nd row0.550000012
3rd row0.790000021
4th row0.889999986
5th row0.879999995
ValueCountFrequency (%)
0.910000026 34
 
7.7%
0.899999976 32
 
7.3%
0.860000014 29
 
6.6%
0.939999998 28
 
6.4%
0.920000017 28
 
6.4%
0.829999983 26
 
5.9%
0.889999986 25
 
5.7%
0.850000024 25
 
5.7%
0.879999995 24
 
5.5%
0.930000007 21
 
4.8%
Other values (24) 168
38.2%
2023-12-09T22:07:00.926017image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1674
34.8%
9 1323
27.5%
. 440
 
9.1%
8 379
 
7.9%
7 221
 
4.6%
2 182
 
3.8%
1 181
 
3.8%
6 134
 
2.8%
3 112
 
2.3%
4 86
 
1.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4377
90.9%
Other Punctuation 440
 
9.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1674
38.2%
9 1323
30.2%
8 379
 
8.7%
7 221
 
5.0%
2 182
 
4.2%
1 181
 
4.1%
6 134
 
3.1%
3 112
 
2.6%
4 86
 
2.0%
5 85
 
1.9%
Other Punctuation
ValueCountFrequency (%)
. 440
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4817
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1674
34.8%
9 1323
27.5%
. 440
 
9.1%
8 379
 
7.9%
7 221
 
4.6%
2 182
 
3.8%
1 181
 
3.8%
6 134
 
2.8%
3 112
 
2.3%
4 86
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4817
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1674
34.8%
9 1323
27.5%
. 440
 
9.1%
8 379
 
7.9%
7 221
 
4.6%
2 182
 
3.8%
1 181
 
3.8%
6 134
 
2.8%
3 112
 
2.3%
4 86
 
1.8%

pct_stu_enough_variety
Text

Distinct58
Distinct (%)13.2%
Missing1
Missing (%)0.2%
Memory size29.1 KiB
2023-12-09T22:07:01.196308image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length11
Median length11
Mean length10.5808656
Min length1

Characters and Unicode

Total characters4645
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique11 ?
Unique (%)2.5%

Sample

1st row0.899999976
2nd row0.899999976
3rd row0.330000013
4th row0.689999998
5th row0.540000021
ValueCountFrequency (%)
0.810000002 28
 
6.4%
0.779999971 20
 
4.6%
0.800000012 19
 
4.3%
0.860000014 19
 
4.3%
0.790000021 19
 
4.3%
0.75 18
 
4.1%
0.74000001 18
 
4.1%
0.850000024 17
 
3.9%
0.879999995 15
 
3.4%
0.839999974 15
 
3.4%
Other values (48) 251
57.2%
2023-12-09T22:07:01.584724image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1630
35.1%
9 1173
25.3%
. 437
 
9.4%
8 310
 
6.7%
7 283
 
6.1%
1 195
 
4.2%
2 167
 
3.6%
6 163
 
3.5%
5 119
 
2.6%
4 94
 
2.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4208
90.6%
Other Punctuation 437
 
9.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1630
38.7%
9 1173
27.9%
8 310
 
7.4%
7 283
 
6.7%
1 195
 
4.6%
2 167
 
4.0%
6 163
 
3.9%
5 119
 
2.8%
4 94
 
2.2%
3 74
 
1.8%
Other Punctuation
ValueCountFrequency (%)
. 437
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4645
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1630
35.1%
9 1173
25.3%
. 437
 
9.4%
8 310
 
6.7%
7 283
 
6.1%
1 195
 
4.2%
2 167
 
3.6%
6 163
 
3.5%
5 119
 
2.6%
4 94
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4645
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1630
35.1%
9 1173
25.3%
. 437
 
9.4%
8 310
 
6.7%
7 283
 
6.1%
1 195
 
4.2%
2 167
 
3.6%
6 163
 
3.5%
5 119
 
2.6%
4 94
 
2.0%

college_career_rate
Text

MISSING 

Distinct275
Distinct (%)74.5%
Missing71
Missing (%)16.1%
Memory size26.7 KiB
2023-12-09T22:07:01.917341image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length11
Median length11
Mean length10.48238482
Min length1

Characters and Unicode

Total characters3868
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique198 ?
Unique (%)53.7%

Sample

1st row0.486000001
2nd row0.389999986
3rd row0.524999976
4th row0.36500001
5th row0.257999986
ValueCountFrequency (%)
0.416000009 4
 
1.1%
0.389999986 4
 
1.1%
0.456 4
 
1.1%
0.467000008 4
 
1.1%
0.5 4
 
1.1%
0.365999997 3
 
0.8%
0.547999978 3
 
0.8%
0.910000026 3
 
0.8%
0.50999999 3
 
0.8%
0.560000002 3
 
0.8%
Other values (265) 334
90.5%
2023-12-09T22:07:02.368378image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1208
31.2%
9 895
23.1%
. 367
 
9.5%
8 192
 
5.0%
7 187
 
4.8%
5 184
 
4.8%
2 175
 
4.5%
4 174
 
4.5%
6 165
 
4.3%
3 163
 
4.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3501
90.5%
Other Punctuation 367
 
9.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1208
34.5%
9 895
25.6%
8 192
 
5.5%
7 187
 
5.3%
5 184
 
5.3%
2 175
 
5.0%
4 174
 
5.0%
6 165
 
4.7%
3 163
 
4.7%
1 158
 
4.5%
Other Punctuation
ValueCountFrequency (%)
. 367
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3868
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1208
31.2%
9 895
23.1%
. 367
 
9.5%
8 192
 
5.0%
7 187
 
4.8%
5 184
 
4.8%
2 175
 
4.5%
4 174
 
4.5%
6 165
 
4.3%
3 163
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3868
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1208
31.2%
9 895
23.1%
. 367
 
9.5%
8 192
 
5.0%
7 187
 
4.8%
5 184
 
4.8%
2 175
 
4.5%
4 174
 
4.5%
6 165
 
4.3%
3 163
 
4.2%

pct_stu_safe
Text

Distinct40
Distinct (%)9.1%
Missing1
Missing (%)0.2%
Memory size29.2 KiB
2023-12-09T22:07:02.638134image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length11
Median length11
Mean length10.70159453
Min length1

Characters and Unicode

Total characters4698
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)1.1%

Sample

1st row0.970000029
2nd row0.959999979
3rd row0.629999995
4th row0.649999976
5th row0.870000005
ValueCountFrequency (%)
0.860000014 31
 
7.1%
0.839999974 25
 
5.7%
0.810000002 24
 
5.5%
0.850000024 22
 
5.0%
0.829999983 20
 
4.6%
0.74000001 19
 
4.3%
0.75999999 19
 
4.3%
0.939999998 19
 
4.3%
0.910000026 19
 
4.3%
0.899999976 18
 
4.1%
Other values (30) 223
50.8%
2023-12-09T22:07:03.021620image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1660
35.3%
9 1254
26.7%
. 436
 
9.3%
8 348
 
7.4%
7 234
 
5.0%
1 188
 
4.0%
2 149
 
3.2%
6 125
 
2.7%
4 111
 
2.4%
3 100
 
2.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4262
90.7%
Other Punctuation 436
 
9.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1660
38.9%
9 1254
29.4%
8 348
 
8.2%
7 234
 
5.5%
1 188
 
4.4%
2 149
 
3.5%
6 125
 
2.9%
4 111
 
2.6%
3 100
 
2.3%
5 93
 
2.2%
Other Punctuation
ValueCountFrequency (%)
. 436
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4698
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1660
35.3%
9 1254
26.7%
. 436
 
9.3%
8 348
 
7.4%
7 234
 
5.0%
1 188
 
4.0%
2 149
 
3.2%
6 125
 
2.7%
4 111
 
2.4%
3 100
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4698
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1660
35.3%
9 1254
26.7%
. 436
 
9.3%
8 348
 
7.4%
7 234
 
5.0%
1 188
 
4.0%
2 149
 
3.2%
6 125
 
2.7%
4 111
 
2.4%
3 100
 
2.1%

girls
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)11.1%
Missing431
Missing (%)98.0%
Memory size14.1 KiB
2023-12-09T22:07:03.141367image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters9
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1
ValueCountFrequency (%)
1 9
100.0%
2023-12-09T22:07:03.354423image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 9
100.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 9
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 9
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 9
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 9
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 9
100.0%

boys
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)25.0%
Missing436
Missing (%)99.1%
Memory size14.0 KiB
2023-12-09T22:07:03.455782image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
ValueCountFrequency (%)
1 4
100.0%
2023-12-09T22:07:03.664283image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 4
100.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 4
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 4
100.0%

pbat
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)2.6%
Missing402
Missing (%)91.4%
Memory size14.8 KiB
2023-12-09T22:07:03.765090image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters38
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1
ValueCountFrequency (%)
1 38
100.0%
2023-12-09T22:07:03.990497image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 38
100.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 38
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 38
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 38
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 38
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 38
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 38
100.0%

international
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)4.5%
Missing418
Missing (%)95.0%
Memory size14.4 KiB
2023-12-09T22:07:04.094443image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters22
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1
ValueCountFrequency (%)
1 22
100.0%
2023-12-09T22:07:04.322469image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 22
100.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 22
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 22
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 22
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 22
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 22
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 22
100.0%

specialized
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)11.1%
Missing431
Missing (%)98.0%
Memory size14.1 KiB
2023-12-09T22:07:04.430778image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters9
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1
ValueCountFrequency (%)
1 9
100.0%
2023-12-09T22:07:04.659318image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 9
100.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 9
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 9
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 9
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 9
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 9
100.0%

transfer
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)9.1%
Missing429
Missing (%)97.5%
Memory size14.2 KiB
2023-12-09T22:07:04.761073image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters11
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1
ValueCountFrequency (%)
1 11
100.0%
2023-12-09T22:07:04.980699image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 11
100.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 11
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 11
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 11
100.0%

ptech
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)14.3%
Missing433
Missing (%)98.4%
Memory size14.1 KiB
2023-12-09T22:07:05.089988image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters7
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1
ValueCountFrequency (%)
1 7
100.0%
2023-12-09T22:07:05.333343image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 7
100.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 7
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 7
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 7
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 7
100.0%

earlycollege
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)5.3%
Missing421
Missing (%)95.7%
Memory size14.4 KiB
2023-12-09T22:07:05.434621image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters19
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1
ValueCountFrequency (%)
1 19
100.0%
2023-12-09T22:07:05.659945image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 19
100.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 19
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 19
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 19
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 19
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 19
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 19
100.0%

geoeligibility
Text

MISSING 

Distinct5
Distinct (%)38.5%
Missing427
Missing (%)97.0%
Memory size14.7 KiB
2023-12-09T22:07:05.855833image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length45
Median length43
Mean length39.38461538
Min length37

Characters and Unicode

Total characters512
Distinct characters26
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)15.4%

Sample

1st rowOpen only to Bronx students/residents
2nd rowOpen only to District 25 students/residents
3rd rowOpen only to Queens students/residents
4th rowOpen only to Staten Island students/residents
5th rowOpen only to Brooklyn students/residents
ValueCountFrequency (%)
open 13
19.4%
only 13
19.4%
to 13
19.4%
students/residents 13
19.4%
queens 5
 
7.5%
brooklyn 4
 
6.0%
bronx 2
 
3.0%
district 1
 
1.5%
25 1
 
1.5%
staten 1
 
1.5%
2023-12-09T22:07:06.211816image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
n 65
12.7%
e 63
12.3%
s 59
11.5%
t 56
10.9%
54
10.5%
o 36
 
7.0%
d 27
 
5.3%
r 20
 
3.9%
l 18
 
3.5%
u 18
 
3.5%
Other values (16) 96
18.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 416
81.2%
Space Separator 54
 
10.5%
Uppercase Letter 27
 
5.3%
Other Punctuation 13
 
2.5%
Decimal Number 2
 
0.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n 65
15.6%
e 63
15.1%
s 59
14.2%
t 56
13.5%
o 36
8.7%
d 27
6.5%
r 20
 
4.8%
l 18
 
4.3%
u 18
 
4.3%
y 17
 
4.1%
Other values (6) 37
8.9%
Uppercase Letter
ValueCountFrequency (%)
O 13
48.1%
B 6
22.2%
Q 5
 
18.5%
D 1
 
3.7%
S 1
 
3.7%
I 1
 
3.7%
Decimal Number
ValueCountFrequency (%)
2 1
50.0%
5 1
50.0%
Space Separator
ValueCountFrequency (%)
54
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 13
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 443
86.5%
Common 69
 
13.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
n 65
14.7%
e 63
14.2%
s 59
13.3%
t 56
12.6%
o 36
8.1%
d 27
6.1%
r 20
 
4.5%
l 18
 
4.1%
u 18
 
4.1%
y 17
 
3.8%
Other values (12) 64
14.4%
Common
ValueCountFrequency (%)
54
78.3%
/ 13
 
18.8%
2 1
 
1.4%
5 1
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 512
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n 65
12.7%
e 63
12.3%
s 59
11.5%
t 56
10.9%
54
10.5%
o 36
 
7.0%
d 27
 
5.3%
r 20
 
3.9%
l 18
 
3.5%
u 18
 
3.5%
Other values (16) 96
18.8%

school_accessibility_description
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)0.3%
Missing114
Missing (%)25.9%
Memory size22.2 KiB
2023-12-09T22:07:06.322074image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters326
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1
ValueCountFrequency (%)
1 326
100.0%
2023-12-09T22:07:06.542642image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 326
100.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 326
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 326
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 326
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 326
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 326
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 326
100.0%

prgdesc1
Text

MISSING 

Distinct203
Distinct (%)97.6%
Missing232
Missing (%)52.7%
Memory size63.2 KiB
2023-12-09T22:07:06.879597image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length499
Median length236.5
Mean length204.1971154
Min length32

Characters and Unicode

Total characters42473
Distinct characters78
Distinct categories11 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique200 ?
Unique (%)96.2%

Sample

1st rowProvides arts instruction to all students and integrates the arts into the core curriculum.
2nd rowIncoming ninth graders will participate in our Ninth Grade Academy, which will allow for a positive transition to a high school setting. At the end of their ninth grade year, students will choose from six career pathways for exploration.
3rd rowProvides ongoing exposure to health science careers. All students are required to take four years of mathematics and science.
4th rowStudy includes text analysis, film as a cultural and historical document, analysis of artist work; courses in video production, film theory and history, industry practices, and legal issues. Students have access to state-of-the-art digital technology.
5th rowComprehensive four-year program that prepares students for collegiate studies in criminal justice as well as careers in law enforcement and emergency response. The program includes Honors and AP courses. Partnerships include Hogan-Lovells Law Firm, NYPD, FDNY, FBI and The Justice Resource Center.
ValueCountFrequency (%)
and 391
 
6.5%
the 208
 
3.5%
in 196
 
3.3%
to 168
 
2.8%
students 162
 
2.7%
of 135
 
2.2%
a 95
 
1.6%
for 76
 
1.3%
program 75
 
1.2%
college 59
 
1.0%
Other values (1331) 4438
73.9%
2023-12-09T22:07:07.419257image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5796
13.6%
e 3872
 
9.1%
i 2905
 
6.8%
n 2861
 
6.7%
t 2783
 
6.6%
a 2706
 
6.4%
r 2467
 
5.8%
o 2466
 
5.8%
s 2430
 
5.7%
c 1678
 
4.0%
Other values (68) 12509
29.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 34079
80.2%
Space Separator 5796
 
13.6%
Uppercase Letter 1405
 
3.3%
Other Punctuation 905
 
2.1%
Dash Punctuation 103
 
0.2%
Decimal Number 92
 
0.2%
Close Punctuation 39
 
0.1%
Open Punctuation 39
 
0.1%
Final Punctuation 8
 
< 0.1%
Math Symbol 6
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 3872
11.4%
i 2905
 
8.5%
n 2861
 
8.4%
t 2783
 
8.2%
a 2706
 
7.9%
r 2467
 
7.2%
o 2466
 
7.2%
s 2430
 
7.1%
c 1678
 
4.9%
l 1489
 
4.4%
Other values (16) 8422
24.7%
Uppercase Letter
ValueCountFrequency (%)
S 244
17.4%
A 196
14.0%
C 132
9.4%
T 122
8.7%
P 103
 
7.3%
E 81
 
5.8%
H 63
 
4.5%
I 58
 
4.1%
M 57
 
4.1%
F 46
 
3.3%
Other values (15) 303
21.6%
Decimal Number
ValueCountFrequency (%)
1 33
35.9%
0 19
20.7%
2 13
 
14.1%
5 6
 
6.5%
6 5
 
5.4%
9 4
 
4.3%
4 4
 
4.3%
3 4
 
4.3%
8 3
 
3.3%
7 1
 
1.1%
Other Punctuation
ValueCountFrequency (%)
, 464
51.3%
. 363
40.1%
; 32
 
3.5%
: 20
 
2.2%
/ 16
 
1.8%
& 7
 
0.8%
% 2
 
0.2%
' 1
 
0.1%
Dash Punctuation
ValueCountFrequency (%)
- 101
98.1%
— 2
 
1.9%
Final Punctuation
ValueCountFrequency (%)
’ 7
87.5%
” 1
 
12.5%
Space Separator
ValueCountFrequency (%)
5796
100.0%
Close Punctuation
ValueCountFrequency (%)
) 39
100.0%
Open Punctuation
ValueCountFrequency (%)
( 39
100.0%
Math Symbol
ValueCountFrequency (%)
+ 6
100.0%
Initial Punctuation
ValueCountFrequency (%)
“ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 35484
83.5%
Common 6989
 
16.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 3872
 
10.9%
i 2905
 
8.2%
n 2861
 
8.1%
t 2783
 
7.8%
a 2706
 
7.6%
r 2467
 
7.0%
o 2466
 
6.9%
s 2430
 
6.8%
c 1678
 
4.7%
l 1489
 
4.2%
Other values (41) 9827
27.7%
Common
ValueCountFrequency (%)
5796
82.9%
, 464
 
6.6%
. 363
 
5.2%
- 101
 
1.4%
) 39
 
0.6%
( 39
 
0.6%
1 33
 
0.5%
; 32
 
0.5%
: 20
 
0.3%
0 19
 
0.3%
Other values (17) 83
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 42451
99.9%
None 11
 
< 0.1%
Punctuation 11
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5796
13.7%
e 3872
 
9.1%
i 2905
 
6.8%
n 2861
 
6.7%
t 2783
 
6.6%
a 2706
 
6.4%
r 2467
 
5.8%
o 2466
 
5.8%
s 2430
 
5.7%
c 1678
 
4.0%
Other values (63) 12487
29.4%
None
ValueCountFrequency (%)
 11
100.0%
Punctuation
ValueCountFrequency (%)
’ 7
63.6%
— 2
 
18.2%
“ 1
 
9.1%
” 1
 
9.1%

prgdesc2
Text

MISSING 

Distinct118
Distinct (%)98.3%
Missing320
Missing (%)72.7%
Memory size49.4 KiB
2023-12-09T22:07:07.827287image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length629
Median length252.5
Mean length241.9833333
Min length22

Characters and Unicode

Total characters29038
Distinct characters77
Distinct categories11 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique116 ?
Unique (%)96.7%

Sample

1st rowThis hybrid-program allows students to study key principles of the legal field and the scientific aspects of forensics. Students engage in learning the scientific technology and lab skills related to the field of Medical Forensics and how this scientific evidence can be utilized by the court system to reinforce the foundations of the American legal system. The curriculum also emphasizes scientific, mathematical, technological, and legal research.
2nd rowHonors-level sequence of courses in science, technology, engineering, and math. This challenging scholastic experience includes preparation for authentic science research and writing in signature national science competitions (Intel, Westinghouse, and Siemens). Students will publish a science journal (non-print) of original science research under the mentorship of leading science teachers, scientists, and publishers.
3rd rowIntensive study of art (theory, production, history, assessment); museum and gallery visits, student exhibitions, visiting artists. Courses – Foundation, 2-D and 3-D Design, Painting, Sculpture, Communication Arts, Print-Making, Portfolio, Digital Photography.
4th rowComprehensive four-year program that prepares students for collegiate studies through service and includes Honors and AP courses. Partnerships include The New York Blood Center, Jewish Home Lifecare, and the Liberty Partnership Program.
5th rowBuilt around the core values: excellence, engagement and empathy. Students take two hours of conservatory-style class daily in acting, movement/devising, voice & speech and theater studies. Each grade also participates in supplementary performance projects including classics, new play commissions and student-created work. Goal is to develop exemplary artists who are equally engaged citizens.
ValueCountFrequency (%)
and 272
 
6.6%
the 144
 
3.5%
in 135
 
3.3%
students 122
 
3.0%
to 95
 
2.3%
of 92
 
2.2%
program 64
 
1.6%
a 62
 
1.5%
for 57
 
1.4%
will 47
 
1.1%
Other values (1160) 3002
73.4%
2023-12-09T22:07:08.414968image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3972
13.7%
e 2564
 
8.8%
i 1989
 
6.8%
n 1978
 
6.8%
t 1905
 
6.6%
a 1798
 
6.2%
o 1683
 
5.8%
r 1682
 
5.8%
s 1680
 
5.8%
c 1058
 
3.6%
Other values (67) 8729
30.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 23182
79.8%
Space Separator 3972
 
13.7%
Uppercase Letter 1058
 
3.6%
Other Punctuation 654
 
2.3%
Dash Punctuation 75
 
0.3%
Decimal Number 42
 
0.1%
Close Punctuation 18
 
0.1%
Open Punctuation 18
 
0.1%
Final Punctuation 13
 
< 0.1%
Math Symbol 5
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 2564
11.1%
i 1989
 
8.6%
n 1978
 
8.5%
t 1905
 
8.2%
a 1798
 
7.8%
o 1683
 
7.3%
r 1682
 
7.3%
s 1680
 
7.2%
c 1058
 
4.6%
l 1041
 
4.5%
Other values (16) 5804
25.0%
Uppercase Letter
ValueCountFrequency (%)
S 146
13.8%
C 112
10.6%
A 108
10.2%
T 90
 
8.5%
P 87
 
8.2%
I 62
 
5.9%
E 58
 
5.5%
M 47
 
4.4%
D 43
 
4.1%
N 42
 
4.0%
Other values (16) 263
24.9%
Decimal Number
ValueCountFrequency (%)
1 12
28.6%
2 8
19.0%
3 7
16.7%
0 5
11.9%
8 5
11.9%
5 2
 
4.8%
9 1
 
2.4%
7 1
 
2.4%
4 1
 
2.4%
Other Punctuation
ValueCountFrequency (%)
, 372
56.9%
. 237
36.2%
& 14
 
2.1%
/ 13
 
2.0%
; 9
 
1.4%
: 7
 
1.1%
' 2
 
0.3%
Dash Punctuation
ValueCountFrequency (%)
- 74
98.7%
– 1
 
1.3%
Final Punctuation
ValueCountFrequency (%)
’ 12
92.3%
” 1
 
7.7%
Space Separator
ValueCountFrequency (%)
3972
100.0%
Close Punctuation
ValueCountFrequency (%)
) 18
100.0%
Open Punctuation
ValueCountFrequency (%)
( 18
100.0%
Math Symbol
ValueCountFrequency (%)
+ 5
100.0%
Initial Punctuation
ValueCountFrequency (%)
“ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 24240
83.5%
Common 4798
 
16.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 2564
 
10.6%
i 1989
 
8.2%
n 1978
 
8.2%
t 1905
 
7.9%
a 1798
 
7.4%
o 1683
 
6.9%
r 1682
 
6.9%
s 1680
 
6.9%
c 1058
 
4.4%
l 1041
 
4.3%
Other values (42) 6862
28.3%
Common
ValueCountFrequency (%)
3972
82.8%
, 372
 
7.8%
. 237
 
4.9%
- 74
 
1.5%
) 18
 
0.4%
( 18
 
0.4%
& 14
 
0.3%
/ 13
 
0.3%
’ 12
 
0.3%
1 12
 
0.3%
Other values (15) 56
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 29008
99.9%
None 15
 
0.1%
Punctuation 15
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3972
13.7%
e 2564
 
8.8%
i 1989
 
6.9%
n 1978
 
6.8%
t 1905
 
6.6%
a 1798
 
6.2%
o 1683
 
5.8%
r 1682
 
5.8%
s 1680
 
5.8%
c 1058
 
3.6%
Other values (62) 8699
30.0%
None
ValueCountFrequency (%)
 15
100.0%
Punctuation
ValueCountFrequency (%)
’ 12
80.0%
“ 1
 
6.7%
” 1
 
6.7%
– 1
 
6.7%

prgdesc3
Text

MISSING 

Distinct70
Distinct (%)100.0%
Missing370
Missing (%)84.1%
Memory size35.3 KiB
2023-12-09T22:07:08.712264image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length500
Median length234.5
Mean length237.7571429
Min length30

Characters and Unicode

Total characters16643
Distinct characters71
Distinct categories10 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique70 ?
Unique (%)100.0%

Sample

1st rowUpon the completion of the Ninth Grade Academy, students can explore career pathways in one of the following areas: Law, Business and Finance, Forensics and Health Sciences, and Engineering.
2nd rowSmall group instruction on orchestral and band instruments; jazz and concert bands, advanced wind ensemble, string and symphonic orchestras, chamber music of all instrument families, theory, ear training, music history and keyboard harmony.
3rd rowClassical Vocal Music students attend conservatory classes in vocal technique, sight reading, musicianship, ear training and ensemble singing. Students study an extensive vocal repertory, music history, theory, performance technique and movement for singers. Students participate in ensemble and solo performances throughout the year.
4th rowStudents who major in visual art learn how to work within a variety of mediums and styles. Students gain an appreciation for visual art and understand its cultural significance.
5th rowUsing professional equipment and trained by experts chefs, students receive intense instruction. Students have opportunities to intern at high-profile restaurants throughout the New York area. Affiliated with C-CAP (Careers through Culinary Arts Program), inter high school competition at Monroe College.
ValueCountFrequency (%)
and 160
 
6.9%
in 79
 
3.4%
the 73
 
3.2%
students 70
 
3.0%
to 60
 
2.6%
of 51
 
2.2%
program 41
 
1.8%
a 32
 
1.4%
for 32
 
1.4%
courses 26
 
1.1%
Other values (757) 1683
73.0%
2023-12-09T22:07:09.722254image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2237
13.4%
e 1504
 
9.0%
i 1156
 
6.9%
n 1136
 
6.8%
t 1088
 
6.5%
a 996
 
6.0%
r 990
 
5.9%
s 984
 
5.9%
o 940
 
5.6%
c 618
 
3.7%
Other values (61) 4994
30.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 13353
80.2%
Space Separator 2237
 
13.4%
Uppercase Letter 577
 
3.5%
Other Punctuation 384
 
2.3%
Dash Punctuation 50
 
0.3%
Close Punctuation 12
 
0.1%
Open Punctuation 12
 
0.1%
Final Punctuation 8
 
< 0.1%
Decimal Number 8
 
< 0.1%
Initial Punctuation 2
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 1504
11.3%
i 1156
 
8.7%
n 1136
 
8.5%
t 1088
 
8.1%
a 996
 
7.5%
r 990
 
7.4%
s 984
 
7.4%
o 940
 
7.0%
c 618
 
4.6%
l 573
 
4.3%
Other values (16) 3368
25.2%
Uppercase Letter
ValueCountFrequency (%)
C 70
12.1%
S 66
11.4%
A 55
 
9.5%
T 48
 
8.3%
P 47
 
8.1%
E 45
 
7.8%
M 29
 
5.0%
I 27
 
4.7%
D 26
 
4.5%
N 24
 
4.2%
Other values (13) 140
24.3%
Other Punctuation
ValueCountFrequency (%)
, 221
57.6%
. 129
33.6%
; 13
 
3.4%
& 11
 
2.9%
: 6
 
1.6%
/ 2
 
0.5%
' 1
 
0.3%
? 1
 
0.3%
Decimal Number
ValueCountFrequency (%)
3 2
25.0%
4 2
25.0%
8 1
12.5%
2 1
12.5%
7 1
12.5%
0 1
12.5%
Dash Punctuation
ValueCountFrequency (%)
- 49
98.0%
— 1
 
2.0%
Final Punctuation
ValueCountFrequency (%)
’ 6
75.0%
” 2
 
25.0%
Space Separator
ValueCountFrequency (%)
2237
100.0%
Close Punctuation
ValueCountFrequency (%)
) 12
100.0%
Open Punctuation
ValueCountFrequency (%)
( 12
100.0%
Initial Punctuation
ValueCountFrequency (%)
“ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 13930
83.7%
Common 2713
 
16.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 1504
 
10.8%
i 1156
 
8.3%
n 1136
 
8.2%
t 1088
 
7.8%
a 996
 
7.2%
r 990
 
7.1%
s 984
 
7.1%
o 940
 
6.7%
c 618
 
4.4%
l 573
 
4.1%
Other values (39) 3945
28.3%
Common
ValueCountFrequency (%)
2237
82.5%
, 221
 
8.1%
. 129
 
4.8%
- 49
 
1.8%
; 13
 
0.5%
) 12
 
0.4%
( 12
 
0.4%
& 11
 
0.4%
: 6
 
0.2%
’ 6
 
0.2%
Other values (12) 17
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 16621
99.9%
None 11
 
0.1%
Punctuation 11
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2237
13.5%
e 1504
 
9.0%
i 1156
 
7.0%
n 1136
 
6.8%
t 1088
 
6.5%
a 996
 
6.0%
r 990
 
6.0%
s 984
 
5.9%
o 940
 
5.7%
c 618
 
3.7%
Other values (56) 4972
29.9%
None
ValueCountFrequency (%)
 11
100.0%
Punctuation
ValueCountFrequency (%)
’ 6
54.5%
” 2
 
18.2%
“ 2
 
18.2%
— 1
 
9.1%

prgdesc4
Text

MISSING 

Distinct50
Distinct (%)100.0%
Missing390
Missing (%)88.6%
Memory size28.8 KiB
2023-12-09T22:07:10.116024image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length493
Median length245
Mean length244.82
Min length30

Characters and Unicode

Total characters12241
Distinct characters70
Distinct categories10 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique50 ?
Unique (%)100.0%

Sample

1st rowStudents perform in the Concert Choir, Chorale, Chamber Singers, musical theatre, Great American Songbook ensemble, opera workshop and participate in cabaret; curriculum includes voice training, music theory, keyboard, sight singing, diction, and audition preparation.
2nd rowIn partnership with The Ailey School, students follow a course of study with a foundation in ballet and classes in Horton technique, modern (Graham-based), jazz and West African dance.
3rd rowStudents majoring in drama study acting techniques and have the opportunity to perform in schoolwide performances.
4th rowMedia students learn about human communication in a digital world through hands-on experience with video, web and radio production. Internships and partnerships available with WABC-7 Eyewitness News, News 12, Fox 5 and BronxNET.
5th rowChallenging courses in writing, research, social sciences, humanities, and the arts.
ValueCountFrequency (%)
and 104
 
6.3%
in 53
 
3.2%
the 52
 
3.1%
students 50
 
3.0%
to 39
 
2.4%
a 33
 
2.0%
of 31
 
1.9%
program 26
 
1.6%
courses 19
 
1.1%
for 18
 
1.1%
Other values (616) 1228
74.3%
2023-12-09T22:07:10.684305image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1603
13.1%
e 1107
 
9.0%
i 858
 
7.0%
n 820
 
6.7%
t 813
 
6.6%
a 760
 
6.2%
s 703
 
5.7%
o 695
 
5.7%
r 678
 
5.5%
c 487
 
4.0%
Other values (60) 3717
30.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 9787
80.0%
Space Separator 1603
 
13.1%
Uppercase Letter 424
 
3.5%
Other Punctuation 350
 
2.9%
Dash Punctuation 38
 
0.3%
Decimal Number 15
 
0.1%
Open Punctuation 9
 
0.1%
Close Punctuation 9
 
0.1%
Final Punctuation 4
 
< 0.1%
Math Symbol 2
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 1107
11.3%
i 858
 
8.8%
n 820
 
8.4%
t 813
 
8.3%
a 760
 
7.8%
s 703
 
7.2%
o 695
 
7.1%
r 678
 
6.9%
c 487
 
5.0%
l 412
 
4.2%
Other values (16) 2454
25.1%
Uppercase Letter
ValueCountFrequency (%)
S 71
16.7%
A 52
12.3%
C 48
11.3%
T 38
9.0%
E 25
 
5.9%
I 24
 
5.7%
P 24
 
5.7%
M 22
 
5.2%
N 16
 
3.8%
D 14
 
3.3%
Other values (14) 90
21.2%
Other Punctuation
ValueCountFrequency (%)
, 213
60.9%
. 107
30.6%
; 10
 
2.9%
/ 7
 
2.0%
: 7
 
2.0%
& 6
 
1.7%
Decimal Number
ValueCountFrequency (%)
3 4
26.7%
1 4
26.7%
2 3
20.0%
0 2
13.3%
7 1
 
6.7%
5 1
 
6.7%
Dash Punctuation
ValueCountFrequency (%)
- 36
94.7%
— 1
 
2.6%
– 1
 
2.6%
Space Separator
ValueCountFrequency (%)
1603
100.0%
Open Punctuation
ValueCountFrequency (%)
( 9
100.0%
Close Punctuation
ValueCountFrequency (%)
) 9
100.0%
Final Punctuation
ValueCountFrequency (%)
’ 4
100.0%
Math Symbol
ValueCountFrequency (%)
+ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 10211
83.4%
Common 2030
 
16.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 1107
 
10.8%
i 858
 
8.4%
n 820
 
8.0%
t 813
 
8.0%
a 760
 
7.4%
s 703
 
6.9%
o 695
 
6.8%
r 678
 
6.6%
c 487
 
4.8%
l 412
 
4.0%
Other values (40) 2878
28.2%
Common
ValueCountFrequency (%)
1603
79.0%
, 213
 
10.5%
. 107
 
5.3%
- 36
 
1.8%
; 10
 
0.5%
( 9
 
0.4%
) 9
 
0.4%
/ 7
 
0.3%
: 7
 
0.3%
& 6
 
0.3%
Other values (10) 23
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 12229
99.9%
None 6
 
< 0.1%
Punctuation 6
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1603
13.1%
e 1107
 
9.1%
i 858
 
7.0%
n 820
 
6.7%
t 813
 
6.6%
a 760
 
6.2%
s 703
 
5.7%
o 695
 
5.7%
r 678
 
5.5%
c 487
 
4.0%
Other values (56) 3705
30.3%
None
ValueCountFrequency (%)
 6
100.0%
Punctuation
ValueCountFrequency (%)
’ 4
66.7%
— 1
 
16.7%
– 1
 
16.7%

prgdesc5
Text

MISSING 

Distinct34
Distinct (%)100.0%
Missing406
Missing (%)92.3%
Memory size24.2 KiB
2023-12-09T22:07:11.038975image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length503
Median length246.5
Mean length259.3529412
Min length69

Characters and Unicode

Total characters8818
Distinct characters65
Distinct categories10 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique34 ?
Unique (%)100.0%

Sample

1st rowBallet, modern dance, dance history, choreography, and dance criticism courses; Jazz, tap, ballroom dancing, kinesiology, anatomy, career management, and dance production classes; students attend live performances and take part in school productions.
2nd rowLearn life skills with a military focus; discipline, respect, and service are the trademarks of our AFJROTC program
3rd rowChallenging courses in the field of pharmaceutical science and internship experience at a local pharmacy to prepare students to major in pharmaceutical science in college.
4th rowInterpretation of dramatic literature, acting, directing, playwriting, improvisation, scenic design, filmmaking and career counseling in the arts.
5th rowInstruction on all vocal, band, and orchestra instruments, beginner and intermediate band, jazz band, orchestra and percussion.
ValueCountFrequency (%)
and 93
 
7.6%
students 48
 
3.9%
in 35
 
2.9%
the 33
 
2.7%
of 27
 
2.2%
to 26
 
2.1%
a 22
 
1.8%
for 17
 
1.4%
program 13
 
1.1%
will 12
 
1.0%
Other values (510) 897
73.3%
2023-12-09T22:07:11.540492image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1189
13.5%
e 735
 
8.3%
t 634
 
7.2%
n 618
 
7.0%
i 610
 
6.9%
a 584
 
6.6%
r 546
 
6.2%
s 489
 
5.5%
o 480
 
5.4%
d 325
 
3.7%
Other values (55) 2608
29.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 7068
80.2%
Space Separator 1189
 
13.5%
Uppercase Letter 276
 
3.1%
Other Punctuation 253
 
2.9%
Dash Punctuation 18
 
0.2%
Decimal Number 4
 
< 0.1%
Close Punctuation 3
 
< 0.1%
Open Punctuation 3
 
< 0.1%
Math Symbol 2
 
< 0.1%
Final Punctuation 2
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 735
10.4%
t 634
 
9.0%
n 618
 
8.7%
i 610
 
8.6%
a 584
 
8.3%
r 546
 
7.7%
s 489
 
6.9%
o 480
 
6.8%
d 325
 
4.6%
c 308
 
4.4%
Other values (16) 1739
24.6%
Uppercase Letter
ValueCountFrequency (%)
S 44
15.9%
C 32
11.6%
A 28
 
10.1%
I 19
 
6.9%
E 18
 
6.5%
T 17
 
6.2%
N 14
 
5.1%
M 13
 
4.7%
R 10
 
3.6%
F 10
 
3.6%
Other values (13) 71
25.7%
Other Punctuation
ValueCountFrequency (%)
, 159
62.8%
. 71
28.1%
; 8
 
3.2%
: 7
 
2.8%
/ 4
 
1.6%
& 3
 
1.2%
! 1
 
0.4%
Decimal Number
ValueCountFrequency (%)
3 2
50.0%
5 1
25.0%
2 1
25.0%
Space Separator
ValueCountFrequency (%)
1189
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 18
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Math Symbol
ValueCountFrequency (%)
+ 2
100.0%
Final Punctuation
ValueCountFrequency (%)
’ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 7344
83.3%
Common 1474
 
16.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 735
 
10.0%
t 634
 
8.6%
n 618
 
8.4%
i 610
 
8.3%
a 584
 
8.0%
r 546
 
7.4%
s 489
 
6.7%
o 480
 
6.5%
d 325
 
4.4%
c 308
 
4.2%
Other values (39) 2015
27.4%
Common
ValueCountFrequency (%)
1189
80.7%
, 159
 
10.8%
. 71
 
4.8%
- 18
 
1.2%
; 8
 
0.5%
: 7
 
0.5%
/ 4
 
0.3%
) 3
 
0.2%
& 3
 
0.2%
( 3
 
0.2%
Other values (6) 9
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8814
> 99.9%
Punctuation 2
 
< 0.1%
None 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1189
13.5%
e 735
 
8.3%
t 634
 
7.2%
n 618
 
7.0%
i 610
 
6.9%
a 584
 
6.6%
r 546
 
6.2%
s 489
 
5.5%
o 480
 
5.4%
d 325
 
3.7%
Other values (53) 2604
29.5%
Punctuation
ValueCountFrequency (%)
’ 2
100.0%
None
ValueCountFrequency (%)
 2
100.0%

prgdesc6
Text

MISSING 

Distinct20
Distinct (%)90.9%
Missing418
Missing (%)95.0%
Memory size20.9 KiB
2023-12-09T22:07:11.951552image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length465
Median length262.5
Mean length261.8636364
Min length31

Characters and Unicode

Total characters5761
Distinct characters66
Distinct categories10 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique19 ?
Unique (%)86.4%

Sample

1st rowA four-year course of study that includes acting technique, scene study, speech for actors, dramatic writing, and course work in performing Shakespeare. The Drama Studio creates mainstage productions each year.
2nd rowFocuses on Mathematics and science to prepare students for careers in Engineering and other technical fields. The curriculum is project-based and includes Engineering Design and Production, Energy applications, Environmental friendly technology and Electricity. We have partnerships with the Architecture, Construction and Engineering Mentor Program.
3rd rowIntroduction to the field of computer science and technology through exploration of engaging technology to help students to develop college and job ready skills in technology
4th rowCTE Law Academy courses include Forensics, Criminal Justice, Criminology, Constitutional Law and Legal Studies; Preparation for public and community careers in legal, federal/state/local government agencies; College credit for selected courses; High School Law Institute at Columbia University and NYU; Participation in New York State Mock Trials, Moot Court competition and Police Explorers; Paid internship opportunities with the Justice Resource Center.
5th rowStudents use an industry standard curriculum (NATEF) that covers all facets of automotive repair. Students will learn Steering and Suspension, Brakes and Electricity/Electronics and Engine Performance. Students must take industry exams for certification. Internships are available for eligible students. Internship partners include Blackler Air, DANA Lincoln/Ford, DemaÂ’s Auto, Gotham Motorcycles, Lombardi Harley Davidson, Max Fleet, Millers Tug & Barge, and MTA.
ValueCountFrequency (%)
and 50
 
6.3%
the 29
 
3.7%
students 26
 
3.3%
in 19
 
2.4%
to 17
 
2.1%
program 16
 
2.0%
a 16
 
2.0%
of 14
 
1.8%
courses 13
 
1.6%
for 12
 
1.5%
Other values (370) 579
73.2%
2023-12-09T22:07:12.510829image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
769
13.3%
e 525
 
9.1%
i 377
 
6.5%
r 372
 
6.5%
t 370
 
6.4%
n 361
 
6.3%
a 361
 
6.3%
o 332
 
5.8%
s 306
 
5.3%
c 259
 
4.5%
Other values (56) 1729
30.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 4623
80.2%
Space Separator 769
 
13.3%
Uppercase Letter 211
 
3.7%
Other Punctuation 133
 
2.3%
Dash Punctuation 14
 
0.2%
Decimal Number 6
 
0.1%
Final Punctuation 2
 
< 0.1%
Close Punctuation 1
 
< 0.1%
Math Symbol 1
 
< 0.1%
Open Punctuation 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 525
11.4%
i 377
 
8.2%
r 372
 
8.0%
t 370
 
8.0%
n 361
 
7.8%
a 361
 
7.8%
o 332
 
7.2%
s 306
 
6.6%
c 259
 
5.6%
l 201
 
4.3%
Other values (16) 1159
25.1%
Uppercase Letter
ValueCountFrequency (%)
A 30
14.2%
S 27
12.8%
T 21
10.0%
C 17
8.1%
P 17
8.1%
E 15
 
7.1%
N 14
 
6.6%
M 12
 
5.7%
L 9
 
4.3%
F 7
 
3.3%
Other values (14) 42
19.9%
Other Punctuation
ValueCountFrequency (%)
, 70
52.6%
. 51
38.3%
; 6
 
4.5%
/ 4
 
3.0%
& 2
 
1.5%
Decimal Number
ValueCountFrequency (%)
8 2
33.3%
7 1
16.7%
9 1
16.7%
0 1
16.7%
1 1
16.7%
Space Separator
ValueCountFrequency (%)
769
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 14
100.0%
Final Punctuation
ValueCountFrequency (%)
’ 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 4834
83.9%
Common 927
 
16.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 525
 
10.9%
i 377
 
7.8%
r 372
 
7.7%
t 370
 
7.7%
n 361
 
7.5%
a 361
 
7.5%
o 332
 
6.9%
s 306
 
6.3%
c 259
 
5.4%
l 201
 
4.2%
Other values (40) 1370
28.3%
Common
ValueCountFrequency (%)
769
83.0%
, 70
 
7.6%
. 51
 
5.5%
- 14
 
1.5%
; 6
 
0.6%
/ 4
 
0.4%
’ 2
 
0.2%
8 2
 
0.2%
& 2
 
0.2%
) 1
 
0.1%
Other values (6) 6
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5757
99.9%
Punctuation 2
 
< 0.1%
None 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
769
13.4%
e 525
 
9.1%
i 377
 
6.5%
r 372
 
6.5%
t 370
 
6.4%
n 361
 
6.3%
a 361
 
6.3%
o 332
 
5.8%
s 306
 
5.3%
c 259
 
4.5%
Other values (54) 1725
30.0%
Punctuation
ValueCountFrequency (%)
’ 2
100.0%
None
ValueCountFrequency (%)
 2
100.0%

prgdesc7
Text

MISSING 

Distinct11
Distinct (%)100.0%
Missing429
Missing (%)97.5%
Memory size17.5 KiB
2023-12-09T22:07:12.851503image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length468
Median length334
Mean length316.7272727
Min length31

Characters and Unicode

Total characters3484
Distinct characters58
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique11 ?
Unique (%)100.0%

Sample

1st rowBiz-tek prepares students for college and careers in a range of business and STEM fields. CTE endorsed programs in Virtual Enterprise, Software Engineering; CAD/CAM-Computer Aided Design/Computer Aided Manufacturing and Information Technology & Computer Networking; training for Cisco certifications, CompTIAA+, Cisco Certified Entry Networking Technician (C-CENT) and Cisco Certified Networking Associate (CCNA).
2nd rowIntegrated program that leads to industry based certification. Students are prepared for entry-level positions in construction trades. Curriculum includes carpentry and mechanical construction and CNC Router and MasterCam production. Students are prepared for college and industry positions. Internship partners include E.B. Pritchard Architecture & Glass, Millers Tug and Barge, NYC Division of School facilities, Scaran HVAC, and RGM Signs.
3rd rowThere are three tracks to the fine arts program: art history (includes visual arts), theater, and technical music. Students take the three-year Art Regents exam. Music students also have the opportunity to participate in New York State School Music Association (NYSSMA) activities while developing their instrumental and vocal skills.
4th rowDual Language programs are designed to integrate English Language Learners with English-proficient students to receive content instruction in English and a target language. This program is open to all students regardless of interest area.
5th rowThe Performing Arts program offers students the opportunity to study dance, theater, or music through a variety of classes that are enriched by after-school performances and partnerships with Roundabout Theater, Battery Dance Company, Theatre for New Audiences, and The College of Staten Island. Course offerings include: IB Dance, Modern Dance, Ballet, Composition, Theatre I, IB Theatre, Chorus, Piano, Guitar, Orchestra, Concert Band, Symphonic Band, and Jazz Band.
ValueCountFrequency (%)
and 30
 
6.3%
students 17
 
3.6%
the 13
 
2.7%
in 13
 
2.7%
to 11
 
2.3%
program 10
 
2.1%
are 10
 
2.1%
for 9
 
1.9%
a 8
 
1.7%
of 8
 
1.7%
Other values (251) 347
72.9%
2023-12-09T22:07:13.313874image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
465
13.3%
e 318
 
9.1%
t 243
 
7.0%
n 229
 
6.6%
r 226
 
6.5%
a 225
 
6.5%
i 224
 
6.4%
s 196
 
5.6%
o 183
 
5.3%
c 121
 
3.5%
Other values (48) 1054
30.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2709
77.8%
Space Separator 465
 
13.3%
Uppercase Letter 198
 
5.7%
Other Punctuation 90
 
2.6%
Dash Punctuation 11
 
0.3%
Close Punctuation 5
 
0.1%
Open Punctuation 5
 
0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 318
11.7%
t 243
 
9.0%
n 229
 
8.5%
r 226
 
8.3%
a 225
 
8.3%
i 224
 
8.3%
s 196
 
7.2%
o 183
 
6.8%
c 121
 
4.5%
d 120
 
4.4%
Other values (16) 624
23.0%
Uppercase Letter
ValueCountFrequency (%)
C 33
16.7%
A 25
12.6%
S 21
10.6%
T 19
9.6%
M 15
7.6%
N 13
 
6.6%
E 13
 
6.6%
B 12
 
6.1%
I 10
 
5.1%
P 7
 
3.5%
Other values (10) 30
15.2%
Other Punctuation
ValueCountFrequency (%)
, 49
54.4%
. 30
33.3%
: 3
 
3.3%
; 3
 
3.3%
& 2
 
2.2%
/ 2
 
2.2%
! 1
 
1.1%
Space Separator
ValueCountFrequency (%)
465
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 11
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2907
83.4%
Common 577
 
16.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 318
 
10.9%
t 243
 
8.4%
n 229
 
7.9%
r 226
 
7.8%
a 225
 
7.7%
i 224
 
7.7%
s 196
 
6.7%
o 183
 
6.3%
c 121
 
4.2%
d 120
 
4.1%
Other values (36) 822
28.3%
Common
ValueCountFrequency (%)
465
80.6%
, 49
 
8.5%
. 30
 
5.2%
- 11
 
1.9%
) 5
 
0.9%
( 5
 
0.9%
: 3
 
0.5%
; 3
 
0.5%
& 2
 
0.3%
/ 2
 
0.3%
Other values (2) 2
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3484
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
465
13.3%
e 318
 
9.1%
t 243
 
7.0%
n 229
 
6.6%
r 226
 
6.5%
a 225
 
6.5%
i 224
 
6.4%
s 196
 
5.6%
o 183
 
5.3%
c 121
 
3.5%
Other values (48) 1054
30.3%

prgdesc8
Text

MISSING 

Distinct4
Distinct (%)80.0%
Missing435
Missing (%)98.9%
Memory size14.7 KiB
2023-12-09T22:07:13.636477image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length377
Median length247
Mean length137
Min length1

Characters and Unicode

Total characters685
Distinct characters46
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)60.0%

Sample

1st row.
2nd rowThe SIS program offers a challenging curriculum in the humanities and the possibility of a student exchange with the Netherlands, Italy, France, and/or Spain. All students are expected to take Advancement Via Individual Determination (AVID), a minimum of four AP classes, four years of a World Language, IB certificate classes, and graduate with a NYS Advanced Regents Diploma.
3rd rowAcademic Comprehensive Program
4th rowAcademic Comprehensive Program
5th rowThis program exposes students to real-world applications of forensic science through hands-on instruction while incorporating this theme in all subject areas. Top level forensics specialists share their experiences on-site and through field study.
ValueCountFrequency (%)
a 5
 
5.1%
program 4
 
4.1%
the 4
 
4.1%
of 4
 
4.1%
and 3
 
3.1%
academic 2
 
2.0%
through 2
 
2.0%
with 2
 
2.0%
comprehensive 2
 
2.0%
all 2
 
2.0%
Other values (62) 68
69.4%
2023-12-09T22:07:14.108907image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
93
13.6%
e 65
 
9.5%
a 48
 
7.0%
i 44
 
6.4%
s 40
 
5.8%
t 39
 
5.7%
n 39
 
5.7%
r 37
 
5.4%
o 33
 
4.8%
c 26
 
3.8%
Other values (36) 221
32.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 537
78.4%
Space Separator 93
 
13.6%
Uppercase Letter 37
 
5.4%
Other Punctuation 13
 
1.9%
Dash Punctuation 3
 
0.4%
Close Punctuation 1
 
0.1%
Open Punctuation 1
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 65
12.1%
a 48
 
8.9%
i 44
 
8.2%
s 40
 
7.4%
t 39
 
7.3%
n 39
 
7.3%
r 37
 
6.9%
o 33
 
6.1%
c 26
 
4.8%
h 23
 
4.3%
Other values (14) 143
26.6%
Uppercase Letter
ValueCountFrequency (%)
A 7
18.9%
I 5
13.5%
S 4
10.8%
D 3
8.1%
T 3
8.1%
P 3
8.1%
V 2
 
5.4%
N 2
 
5.4%
C 2
 
5.4%
Y 1
 
2.7%
Other values (5) 5
13.5%
Other Punctuation
ValueCountFrequency (%)
, 7
53.8%
. 5
38.5%
/ 1
 
7.7%
Space Separator
ValueCountFrequency (%)
93
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 574
83.8%
Common 111
 
16.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 65
 
11.3%
a 48
 
8.4%
i 44
 
7.7%
s 40
 
7.0%
t 39
 
6.8%
n 39
 
6.8%
r 37
 
6.4%
o 33
 
5.7%
c 26
 
4.5%
h 23
 
4.0%
Other values (29) 180
31.4%
Common
ValueCountFrequency (%)
93
83.8%
, 7
 
6.3%
. 5
 
4.5%
- 3
 
2.7%
) 1
 
0.9%
( 1
 
0.9%
/ 1
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 685
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
93
13.6%
e 65
 
9.5%
a 48
 
7.0%
i 44
 
6.4%
s 40
 
5.8%
t 39
 
5.7%
n 39
 
5.7%
r 37
 
5.4%
o 33
 
4.8%
c 26
 
3.8%
Other values (36) 221
32.3%

prgdesc9
Text

MISSING 

Distinct2
Distinct (%)100.0%
Missing438
Missing (%)99.5%
Memory size14.3 KiB
2023-12-09T22:07:14.380677image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length337
Median length183.5
Mean length183.5
Min length30

Characters and Unicode

Total characters367
Distinct characters40
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st rowThe Visual Arts program offers students the opportunity to study fine arts or graphic design through a variety of classes that are enriched by after-school programs and a design partnership with Roundabout Theater. Course offerings include: Drawing, Painting, AP Art History, IB Art, and/or CTE Graphic Design using Adobe Creative Suite.
2nd rowComprehensive Academic Program
ValueCountFrequency (%)
design 3
 
5.6%
graphic 2
 
3.7%
art 2
 
3.7%
a 2
 
3.7%
the 2
 
3.7%
arts 2
 
3.7%
program 2
 
3.7%
suite 1
 
1.9%
theater 1
 
1.9%
course 1
 
1.9%
Other values (36) 36
66.7%
2023-12-09T22:07:14.772441image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
52
14.2%
r 30
 
8.2%
e 28
 
7.6%
t 24
 
6.5%
i 23
 
6.3%
a 23
 
6.3%
s 21
 
5.7%
o 20
 
5.4%
n 18
 
4.9%
h 13
 
3.5%
Other values (30) 115
31.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 280
76.3%
Space Separator 52
 
14.2%
Uppercase Letter 26
 
7.1%
Other Punctuation 8
 
2.2%
Dash Punctuation 1
 
0.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
r 30
10.7%
e 28
10.0%
t 24
 
8.6%
i 23
 
8.2%
a 23
 
8.2%
s 21
 
7.5%
o 20
 
7.1%
n 18
 
6.4%
h 13
 
4.6%
g 12
 
4.3%
Other values (11) 68
24.3%
Uppercase Letter
ValueCountFrequency (%)
A 6
23.1%
C 4
15.4%
P 3
11.5%
T 3
11.5%
D 2
 
7.7%
R 1
 
3.8%
V 1
 
3.8%
H 1
 
3.8%
I 1
 
3.8%
B 1
 
3.8%
Other values (3) 3
11.5%
Other Punctuation
ValueCountFrequency (%)
, 4
50.0%
. 2
25.0%
: 1
 
12.5%
/ 1
 
12.5%
Space Separator
ValueCountFrequency (%)
52
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 306
83.4%
Common 61
 
16.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
r 30
 
9.8%
e 28
 
9.2%
t 24
 
7.8%
i 23
 
7.5%
a 23
 
7.5%
s 21
 
6.9%
o 20
 
6.5%
n 18
 
5.9%
h 13
 
4.2%
g 12
 
3.9%
Other values (24) 94
30.7%
Common
ValueCountFrequency (%)
52
85.2%
, 4
 
6.6%
. 2
 
3.3%
- 1
 
1.6%
: 1
 
1.6%
/ 1
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 367
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
52
14.2%
r 30
 
8.2%
e 28
 
7.6%
t 24
 
6.5%
i 23
 
6.3%
a 23
 
6.3%
s 21
 
5.7%
o 20
 
5.4%
n 18
 
4.9%
h 13
 
3.5%
Other values (30) 115
31.3%

prgdesc10
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing439
Missing (%)99.8%
Memory size13.9 KiB
2023-12-09T22:07:14.957047image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length30
Median length30
Mean length30
Min length30

Characters and Unicode

Total characters30
Distinct characters18
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowComprehensive Academic Program
ValueCountFrequency (%)
comprehensive 1
33.3%
academic 1
33.3%
program 1
33.3%
2023-12-09T22:07:15.261881image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 4
13.3%
m 3
 
10.0%
r 3
 
10.0%
i 2
 
6.7%
2
 
6.7%
a 2
 
6.7%
c 2
 
6.7%
o 2
 
6.7%
P 1
 
3.3%
d 1
 
3.3%
Other values (8) 8
26.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 25
83.3%
Uppercase Letter 3
 
10.0%
Space Separator 2
 
6.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 4
16.0%
m 3
12.0%
r 3
12.0%
i 2
8.0%
a 2
8.0%
c 2
8.0%
o 2
8.0%
d 1
 
4.0%
v 1
 
4.0%
s 1
 
4.0%
Other values (4) 4
16.0%
Uppercase Letter
ValueCountFrequency (%)
P 1
33.3%
A 1
33.3%
C 1
33.3%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 28
93.3%
Common 2
 
6.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 4
14.3%
m 3
10.7%
r 3
10.7%
i 2
 
7.1%
a 2
 
7.1%
c 2
 
7.1%
o 2
 
7.1%
P 1
 
3.6%
d 1
 
3.6%
A 1
 
3.6%
Other values (7) 7
25.0%
Common
ValueCountFrequency (%)
2
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 30
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 4
13.3%
m 3
 
10.0%
r 3
 
10.0%
i 2
 
6.7%
2
 
6.7%
a 2
 
6.7%
c 2
 
6.7%
o 2
 
6.7%
P 1
 
3.3%
d 1
 
3.3%
Other values (8) 8
26.7%

directions1
Text

MISSING 

Distinct28
Distinct (%)71.8%
Missing401
Missing (%)91.1%
Memory size19.1 KiB
2023-12-09T22:07:15.623488image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length270
Median length184
Mean length100.8461538
Min length26

Characters and Unicode

Total characters3933
Distinct characters66
Distinct categories9 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique26 ?
Unique (%)66.7%

Sample

1st rowSee theclintonschool.net for more information.
2nd rowStudents must attend an Open House and personalized intake meeting. To find out about open houses, students should call the school at 718-946-6812 or visit our website.
3rd rowPlease contact the school about the on-site requirement.
4th rowStudents must attend an Open House and personalized intake meeting. Please contact the school for open house dates or to schedule a visit
5th rowOn-site requirement occurs at school's Open House.
ValueCountFrequency (%)
the 44
 
7.7%
please 22
 
3.8%
contact 20
 
3.5%
school 19
 
3.3%
and 15
 
2.6%
open 15
 
2.6%
for 14
 
2.4%
an 14
 
2.4%
requirement 13
 
2.3%
at 13
 
2.3%
Other values (192) 385
67.1%
2023-12-09T22:07:16.138459image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
537
13.7%
e 416
 
10.6%
t 327
 
8.3%
o 286
 
7.3%
n 257
 
6.5%
a 226
 
5.7%
s 217
 
5.5%
i 194
 
4.9%
r 173
 
4.4%
c 146
 
3.7%
Other values (56) 1154
29.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 3081
78.3%
Space Separator 537
 
13.7%
Uppercase Letter 122
 
3.1%
Other Punctuation 89
 
2.3%
Decimal Number 71
 
1.8%
Dash Punctuation 23
 
0.6%
Open Punctuation 4
 
0.1%
Close Punctuation 4
 
0.1%
Final Punctuation 2
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 416
13.5%
t 327
10.6%
o 286
9.3%
n 257
 
8.3%
a 226
 
7.3%
s 217
 
7.0%
i 194
 
6.3%
r 173
 
5.6%
c 146
 
4.7%
l 127
 
4.1%
Other values (15) 712
23.1%
Uppercase Letter
ValueCountFrequency (%)
P 25
20.5%
S 17
13.9%
O 16
13.1%
H 13
10.7%
I 7
 
5.7%
T 7
 
5.7%
L 5
 
4.1%
A 5
 
4.1%
M 4
 
3.3%
C 4
 
3.3%
Other values (9) 19
15.6%
Decimal Number
ValueCountFrequency (%)
7 12
16.9%
1 12
16.9%
8 9
12.7%
0 7
9.9%
2 6
8.5%
4 6
8.5%
3 6
8.5%
9 5
7.0%
6 5
7.0%
5 3
 
4.2%
Other Punctuation
ValueCountFrequency (%)
. 68
76.4%
, 9
 
10.1%
' 4
 
4.5%
@ 3
 
3.4%
: 2
 
2.2%
/ 2
 
2.2%
; 1
 
1.1%
Space Separator
ValueCountFrequency (%)
537
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 23
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Final Punctuation
ValueCountFrequency (%)
’ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 3203
81.4%
Common 730
 
18.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 416
13.0%
t 327
 
10.2%
o 286
 
8.9%
n 257
 
8.0%
a 226
 
7.1%
s 217
 
6.8%
i 194
 
6.1%
r 173
 
5.4%
c 146
 
4.6%
l 127
 
4.0%
Other values (34) 834
26.0%
Common
ValueCountFrequency (%)
537
73.6%
. 68
 
9.3%
- 23
 
3.2%
7 12
 
1.6%
1 12
 
1.6%
, 9
 
1.2%
8 9
 
1.2%
0 7
 
1.0%
2 6
 
0.8%
4 6
 
0.8%
Other values (12) 41
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3929
99.9%
None 2
 
0.1%
Punctuation 2
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
537
13.7%
e 416
 
10.6%
t 327
 
8.3%
o 286
 
7.3%
n 257
 
6.5%
a 226
 
5.8%
s 217
 
5.5%
i 194
 
4.9%
r 173
 
4.4%
c 146
 
3.7%
Other values (54) 1150
29.3%
None
ValueCountFrequency (%)
 2
100.0%
Punctuation
ValueCountFrequency (%)
’ 2
100.0%

directions2
Text

MISSING 

Distinct7
Distinct (%)77.8%
Missing431
Missing (%)98.0%
Memory size14.9 KiB
2023-12-09T22:07:16.446719image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length217
Median length133
Mean length95
Min length46

Characters and Unicode

Total characters855
Distinct characters33
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)66.7%

Sample

1st rowStudents are directly contacted by the school and will receive notification by mail and or by phone. It is important that the latest contact information listed for all applicants is correct so that we can contact you.
2nd rowApplicants who meet the criteria for the screened program will be contacted to come in for an interview. Interviews are typically held after school and weekends.
3rd rowPlease contact the school about the on-site requirement.
4th rowStudents can schedule a school tour or interview during Open House dates. Speak with your guidance counselor to make an appointment.
5th rowPlease contact the school about the on-site requirement.
ValueCountFrequency (%)
the 11
 
8.3%
school 7
 
5.3%
contact 6
 
4.5%
for 5
 
3.8%
please 4
 
3.0%
on-site 4
 
3.0%
requirement 4
 
3.0%
will 3
 
2.3%
students 3
 
2.3%
and 3
 
2.3%
Other values (61) 82
62.1%
2023-12-09T22:07:16.883202image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
124
14.5%
e 91
10.6%
t 80
 
9.4%
o 64
 
7.5%
n 52
 
6.1%
a 50
 
5.8%
c 47
 
5.5%
i 46
 
5.4%
s 42
 
4.9%
r 40
 
4.7%
Other values (23) 219
25.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 699
81.8%
Space Separator 124
 
14.5%
Uppercase Letter 16
 
1.9%
Other Punctuation 12
 
1.4%
Dash Punctuation 4
 
0.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 91
13.0%
t 80
11.4%
o 64
9.2%
n 52
 
7.4%
a 50
 
7.2%
c 47
 
6.7%
i 46
 
6.6%
s 42
 
6.0%
r 40
 
5.7%
l 33
 
4.7%
Other values (13) 154
22.0%
Uppercase Letter
ValueCountFrequency (%)
P 4
25.0%
O 3
18.8%
S 3
18.8%
A 2
12.5%
H 2
12.5%
I 2
12.5%
Other Punctuation
ValueCountFrequency (%)
. 11
91.7%
' 1
 
8.3%
Space Separator
ValueCountFrequency (%)
124
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 715
83.6%
Common 140
 
16.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 91
12.7%
t 80
11.2%
o 64
 
9.0%
n 52
 
7.3%
a 50
 
7.0%
c 47
 
6.6%
i 46
 
6.4%
s 42
 
5.9%
r 40
 
5.6%
l 33
 
4.6%
Other values (19) 170
23.8%
Common
ValueCountFrequency (%)
124
88.6%
. 11
 
7.9%
- 4
 
2.9%
' 1
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 855
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
124
14.5%
e 91
10.6%
t 80
 
9.4%
o 64
 
7.5%
n 52
 
6.1%
a 50
 
5.8%
c 47
 
5.5%
i 46
 
5.4%
s 42
 
4.9%
r 40
 
4.7%
Other values (23) 219
25.6%

directions3
Text

MISSING 

Distinct4
Distinct (%)100.0%
Missing436
Missing (%)99.1%
Memory size14.3 KiB
2023-12-09T22:07:17.143859image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length133
Median length68
Mean length78.75
Min length46

Characters and Unicode

Total characters315
Distinct characters31
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)100.0%

Sample

1st rowStudents can schedule a school tour or interview during Open House dates. Speak with your guidance counselor to make an appointment.
2nd rowPlease contact the school for interview dates.
3rd rowPlease contact the school about the on-site requirement.
4th rowAcademic information will be considered for students who successfully auditioned
ValueCountFrequency (%)
the 3
 
6.5%
school 3
 
6.5%
please 2
 
4.3%
for 2
 
4.3%
interview 2
 
4.3%
dates 2
 
4.3%
contact 2
 
4.3%
students 2
 
4.3%
counselor 1
 
2.2%
speak 1
 
2.2%
Other values (26) 26
56.5%
2023-12-09T22:07:17.516458image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
43
13.7%
e 34
 
10.8%
o 25
 
7.9%
t 25
 
7.9%
n 20
 
6.3%
s 18
 
5.7%
a 17
 
5.4%
i 17
 
5.4%
c 16
 
5.1%
u 14
 
4.4%
Other values (21) 86
27.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 260
82.5%
Space Separator 43
 
13.7%
Uppercase Letter 7
 
2.2%
Other Punctuation 4
 
1.3%
Dash Punctuation 1
 
0.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 34
13.1%
o 25
9.6%
t 25
9.6%
n 20
 
7.7%
s 18
 
6.9%
a 17
 
6.5%
i 17
 
6.5%
c 16
 
6.2%
u 14
 
5.4%
r 13
 
5.0%
Other values (13) 61
23.5%
Uppercase Letter
ValueCountFrequency (%)
S 2
28.6%
P 2
28.6%
O 1
14.3%
A 1
14.3%
H 1
14.3%
Space Separator
ValueCountFrequency (%)
43
100.0%
Other Punctuation
ValueCountFrequency (%)
. 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 267
84.8%
Common 48
 
15.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 34
12.7%
o 25
 
9.4%
t 25
 
9.4%
n 20
 
7.5%
s 18
 
6.7%
a 17
 
6.4%
i 17
 
6.4%
c 16
 
6.0%
u 14
 
5.2%
r 13
 
4.9%
Other values (18) 68
25.5%
Common
ValueCountFrequency (%)
43
89.6%
. 4
 
8.3%
- 1
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 315
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
43
13.7%
e 34
 
10.8%
o 25
 
7.9%
t 25
 
7.9%
n 20
 
6.3%
s 18
 
5.7%
a 17
 
5.4%
i 17
 
5.4%
c 16
 
5.1%
u 14
 
4.4%
Other values (21) 86
27.3%

directions4
Text

MISSING 

Distinct3
Distinct (%)100.0%
Missing437
Missing (%)99.3%
Memory size14.2 KiB
2023-12-09T22:07:17.757276image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length133
Median length80
Mean length86.33333333
Min length46

Characters and Unicode

Total characters259
Distinct characters29
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)100.0%

Sample

1st rowStudents can schedule a school tour or interview during Open House dates. Speak with your guidance counselor to make an appointment.
2nd rowPlease contact the school for interview dates.
3rd rowAcademic information will be considered for students who successfully auditioned
ValueCountFrequency (%)
students 2
 
5.3%
school 2
 
5.3%
for 2
 
5.3%
interview 2
 
5.3%
dates 2
 
5.3%
please 1
 
2.6%
during 1
 
2.6%
open 1
 
2.6%
house 1
 
2.6%
speak 1
 
2.6%
Other values (23) 23
60.5%
2023-12-09T22:07:18.115303image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
36
13.9%
e 26
 
10.0%
o 20
 
7.7%
t 18
 
6.9%
n 17
 
6.6%
s 15
 
5.8%
i 15
 
5.8%
a 14
 
5.4%
c 13
 
5.0%
u 12
 
4.6%
Other values (19) 73
28.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 214
82.6%
Space Separator 36
 
13.9%
Uppercase Letter 6
 
2.3%
Other Punctuation 3
 
1.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 26
12.1%
o 20
 
9.3%
t 18
 
8.4%
n 17
 
7.9%
s 15
 
7.0%
i 15
 
7.0%
a 14
 
6.5%
c 13
 
6.1%
u 12
 
5.6%
d 12
 
5.6%
Other values (12) 52
24.3%
Uppercase Letter
ValueCountFrequency (%)
S 2
33.3%
O 1
16.7%
A 1
16.7%
H 1
16.7%
P 1
16.7%
Space Separator
ValueCountFrequency (%)
36
100.0%
Other Punctuation
ValueCountFrequency (%)
. 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 220
84.9%
Common 39
 
15.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 26
11.8%
o 20
 
9.1%
t 18
 
8.2%
n 17
 
7.7%
s 15
 
6.8%
i 15
 
6.8%
a 14
 
6.4%
c 13
 
5.9%
u 12
 
5.5%
d 12
 
5.5%
Other values (17) 58
26.4%
Common
ValueCountFrequency (%)
36
92.3%
. 3
 
7.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 259
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
36
13.9%
e 26
 
10.0%
o 20
 
7.7%
t 18
 
6.9%
n 17
 
6.6%
s 15
 
5.8%
i 15
 
5.8%
a 14
 
5.4%
c 13
 
5.0%
u 12
 
4.6%
Other values (19) 73
28.2%

directions5
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing439
Missing (%)99.8%
Memory size14.0 KiB
2023-12-09T22:07:18.323029image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length80
Median length80
Mean length80
Min length80

Characters and Unicode

Total characters80
Distinct characters20
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowAcademic information will be considered for students who successfully auditioned
ValueCountFrequency (%)
academic 1
10.0%
information 1
10.0%
will 1
10.0%
be 1
10.0%
considered 1
10.0%
for 1
10.0%
students 1
10.0%
who 1
10.0%
successfully 1
10.0%
auditioned 1
10.0%
2023-12-09T22:07:18.642606image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9
11.2%
e 7
 
8.8%
i 7
 
8.8%
o 6
 
7.5%
s 6
 
7.5%
d 6
 
7.5%
c 5
 
6.2%
n 5
 
6.2%
u 4
 
5.0%
t 4
 
5.0%
Other values (10) 21
26.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 70
87.5%
Space Separator 9
 
11.2%
Uppercase Letter 1
 
1.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 7
10.0%
i 7
10.0%
o 6
 
8.6%
s 6
 
8.6%
d 6
 
8.6%
c 5
 
7.1%
n 5
 
7.1%
u 4
 
5.7%
t 4
 
5.7%
l 4
 
5.7%
Other values (8) 16
22.9%
Space Separator
ValueCountFrequency (%)
9
100.0%
Uppercase Letter
ValueCountFrequency (%)
A 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 71
88.8%
Common 9
 
11.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 7
9.9%
i 7
9.9%
o 6
 
8.5%
s 6
 
8.5%
d 6
 
8.5%
c 5
 
7.0%
n 5
 
7.0%
u 4
 
5.6%
t 4
 
5.6%
l 4
 
5.6%
Other values (9) 17
23.9%
Common
ValueCountFrequency (%)
9
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 80
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
9
11.2%
e 7
 
8.8%
i 7
 
8.8%
o 6
 
7.5%
s 6
 
7.5%
d 6
 
7.5%
c 5
 
6.2%
n 5
 
6.2%
u 4
 
5.0%
t 4
 
5.0%
Other values (10) 21
26.2%

directions6
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing439
Missing (%)99.8%
Memory size14.0 KiB
2023-12-09T22:07:18.850049image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length80
Median length80
Mean length80
Min length80

Characters and Unicode

Total characters80
Distinct characters20
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowAcademic information will be considered for students who successfully auditioned
ValueCountFrequency (%)
academic 1
10.0%
information 1
10.0%
will 1
10.0%
be 1
10.0%
considered 1
10.0%
for 1
10.0%
students 1
10.0%
who 1
10.0%
successfully 1
10.0%
auditioned 1
10.0%
2023-12-09T22:07:19.173652image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9
11.2%
e 7
 
8.8%
i 7
 
8.8%
o 6
 
7.5%
s 6
 
7.5%
d 6
 
7.5%
c 5
 
6.2%
n 5
 
6.2%
u 4
 
5.0%
t 4
 
5.0%
Other values (10) 21
26.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 70
87.5%
Space Separator 9
 
11.2%
Uppercase Letter 1
 
1.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 7
10.0%
i 7
10.0%
o 6
 
8.6%
s 6
 
8.6%
d 6
 
8.6%
c 5
 
7.1%
n 5
 
7.1%
u 4
 
5.7%
t 4
 
5.7%
l 4
 
5.7%
Other values (8) 16
22.9%
Space Separator
ValueCountFrequency (%)
9
100.0%
Uppercase Letter
ValueCountFrequency (%)
A 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 71
88.8%
Common 9
 
11.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 7
9.9%
i 7
9.9%
o 6
 
8.5%
s 6
 
8.5%
d 6
 
8.5%
c 5
 
7.0%
n 5
 
7.0%
u 4
 
5.6%
t 4
 
5.6%
l 4
 
5.6%
Other values (9) 17
23.9%
Common
ValueCountFrequency (%)
9
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 80
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
9
11.2%
e 7
 
8.8%
i 7
 
8.8%
o 6
 
7.5%
s 6
 
7.5%
d 6
 
7.5%
c 5
 
6.2%
n 5
 
6.2%
u 4
 
5.0%
t 4
 
5.0%
Other values (10) 21
26.2%

directions7
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing439
Missing (%)99.8%
Memory size14.0 KiB
2023-12-09T22:07:19.357674image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length56
Median length56
Mean length56
Min length56

Characters and Unicode

Total characters56
Distinct characters24
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowPlease Contact the School About the On-Site Requirement.
ValueCountFrequency (%)
the 2
25.0%
please 1
12.5%
contact 1
12.5%
school 1
12.5%
about 1
12.5%
on-site 1
12.5%
requirement 1
12.5%
2023-12-09T22:07:19.648915image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 8
14.3%
t 7
12.5%
7
12.5%
o 4
 
7.1%
n 3
 
5.4%
h 3
 
5.4%
u 2
 
3.6%
l 2
 
3.6%
c 2
 
3.6%
S 2
 
3.6%
Other values (14) 16
28.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 40
71.4%
Space Separator 7
 
12.5%
Uppercase Letter 7
 
12.5%
Dash Punctuation 1
 
1.8%
Other Punctuation 1
 
1.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 8
20.0%
t 7
17.5%
o 4
10.0%
n 3
 
7.5%
h 3
 
7.5%
u 2
 
5.0%
l 2
 
5.0%
c 2
 
5.0%
a 2
 
5.0%
i 2
 
5.0%
Other values (5) 5
12.5%
Uppercase Letter
ValueCountFrequency (%)
S 2
28.6%
R 1
14.3%
P 1
14.3%
O 1
14.3%
A 1
14.3%
C 1
14.3%
Space Separator
ValueCountFrequency (%)
7
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 47
83.9%
Common 9
 
16.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 8
17.0%
t 7
14.9%
o 4
 
8.5%
n 3
 
6.4%
h 3
 
6.4%
u 2
 
4.3%
l 2
 
4.3%
c 2
 
4.3%
S 2
 
4.3%
a 2
 
4.3%
Other values (11) 12
25.5%
Common
ValueCountFrequency (%)
7
77.8%
- 1
 
11.1%
. 1
 
11.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 56
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 8
14.3%
t 7
12.5%
7
12.5%
o 4
 
7.1%
n 3
 
5.4%
h 3
 
5.4%
u 2
 
3.6%
l 2
 
3.6%
c 2
 
3.6%
S 2
 
3.6%
Other values (14) 16
28.6%

directions8
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing440
Missing (%)100.0%
Memory size3.6 KiB

directions9
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing440
Missing (%)100.0%
Memory size3.6 KiB

directions10
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing440
Missing (%)100.0%
Memory size3.6 KiB

requirement1_1
Text

MISSING 

Distinct94
Distinct (%)75.8%
Missing316
Missing (%)71.8%
Memory size25.5 KiB
2023-12-09T22:07:19.920698image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length102
Median length89
Mean length70.85483871
Min length8

Characters and Unicode

Total characters8786
Distinct characters62
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique87 ?
Unique (%)70.2%

Sample

1st rowCourse Grades: English (87-100), Math (83-100), Social Studies (90-100), Science (88-100)
2nd rowDemonstrated Interest: School Visit
3rd rowCourse Grades: English (70-100), Math (70-100), Social Studies (70-100), Science (75-100)
4th rowCourse Grades: English (84-100), Math (71-100), Social Studies (83-100), Science (80-100)
5th rowCourse Grades: English (70-100), Math (70-100), Social Studies (72-100), Science (75-100)
ValueCountFrequency (%)
course 87
 
7.9%
math 87
 
7.9%
grades 85
 
7.8%
english 85
 
7.8%
science 83
 
7.6%
social 82
 
7.5%
studies 82
 
7.5%
85-100 30
 
2.7%
65-100 30
 
2.7%
75-100 27
 
2.5%
Other values (103) 418
38.1%
2023-12-09T22:07:20.344697image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
972
 
11.1%
0 674
 
7.7%
e 578
 
6.6%
i 432
 
4.9%
s 431
 
4.9%
t 340
 
3.9%
1 331
 
3.8%
a 322
 
3.7%
) 311
 
3.5%
( 311
 
3.5%
Other values (52) 4084
46.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 4189
47.7%
Decimal Number 1560
 
17.8%
Space Separator 972
 
11.1%
Uppercase Letter 737
 
8.4%
Other Punctuation 396
 
4.5%
Close Punctuation 311
 
3.5%
Open Punctuation 311
 
3.5%
Dash Punctuation 310
 
3.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 578
13.8%
i 432
10.3%
s 431
10.3%
t 340
8.1%
a 322
7.7%
c 293
 
7.0%
n 266
 
6.3%
o 264
 
6.3%
r 263
 
6.3%
d 221
 
5.3%
Other values (15) 779
18.6%
Uppercase Letter
ValueCountFrequency (%)
S 278
37.7%
C 92
 
12.5%
M 89
 
12.1%
G 87
 
11.8%
E 86
 
11.7%
I 29
 
3.9%
D 21
 
2.8%
V 21
 
2.8%
A 12
 
1.6%
T 6
 
0.8%
Other values (6) 16
 
2.2%
Decimal Number
ValueCountFrequency (%)
0 674
43.2%
1 331
21.2%
5 143
 
9.2%
8 127
 
8.1%
7 112
 
7.2%
6 73
 
4.7%
9 33
 
2.1%
4 28
 
1.8%
2 20
 
1.3%
3 19
 
1.2%
Other Punctuation
ValueCountFrequency (%)
, 257
64.9%
: 115
29.0%
. 14
 
3.5%
% 7
 
1.8%
; 1
 
0.3%
/ 1
 
0.3%
' 1
 
0.3%
Space Separator
ValueCountFrequency (%)
972
100.0%
Close Punctuation
ValueCountFrequency (%)
) 311
100.0%
Open Punctuation
ValueCountFrequency (%)
( 311
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 310
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 4926
56.1%
Common 3860
43.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 578
 
11.7%
i 432
 
8.8%
s 431
 
8.7%
t 340
 
6.9%
a 322
 
6.5%
c 293
 
5.9%
S 278
 
5.6%
n 266
 
5.4%
o 264
 
5.4%
r 263
 
5.3%
Other values (31) 1459
29.6%
Common
ValueCountFrequency (%)
972
25.2%
0 674
17.5%
1 331
 
8.6%
) 311
 
8.1%
( 311
 
8.1%
- 310
 
8.0%
, 257
 
6.7%
5 143
 
3.7%
8 127
 
3.3%
: 115
 
3.0%
Other values (11) 309
 
8.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8786
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
972
 
11.1%
0 674
 
7.7%
e 578
 
6.6%
i 432
 
4.9%
s 431
 
4.9%
t 340
 
3.9%
1 331
 
3.8%
a 322
 
3.7%
) 311
 
3.5%
( 311
 
3.5%
Other values (52) 4084
46.5%

requirement1_2
Text

MISSING 

Distinct40
Distinct (%)70.2%
Missing383
Missing (%)87.0%
Memory size19.2 KiB
2023-12-09T22:07:20.639902image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length89
Median length89
Mean length70.49122807
Min length8

Characters and Unicode

Total characters4018
Distinct characters47
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique35 ?
Unique (%)61.4%

Sample

1st rowCourse Grades: Math (55-100), Science (55-100)
2nd rowCourse Grades: English (78-100), Math (75-100), Social Studies (80-100), Science (80-100)
3rd rowDemonstrated Interest: School Visit
4th rowCourse Grades: English (80-100), Math (70-100), Social Studies (73-100), Science (74-100)
5th rowCourse Grades: English (69-100), Math (65-100), Social Studies (63-100), Science (73-100)
ValueCountFrequency (%)
math 43
 
8.6%
course 42
 
8.4%
grades 41
 
8.2%
english 41
 
8.2%
science 41
 
8.2%
social 40
 
8.0%
studies 40
 
8.0%
55-100 25
 
5.0%
65-100 22
 
4.4%
70-100 12
 
2.4%
Other values (55) 153
30.6%
2023-12-09T22:07:21.095825image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
443
 
11.0%
0 322
 
8.0%
e 255
 
6.3%
i 200
 
5.0%
s 199
 
5.0%
1 150
 
3.7%
) 149
 
3.7%
- 149
 
3.7%
( 149
 
3.7%
a 145
 
3.6%
Other values (37) 1857
46.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1864
46.4%
Decimal Number 744
 
18.5%
Space Separator 443
 
11.0%
Uppercase Letter 338
 
8.4%
Other Punctuation 182
 
4.5%
Close Punctuation 149
 
3.7%
Dash Punctuation 149
 
3.7%
Open Punctuation 149
 
3.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 255
13.7%
i 200
10.7%
s 199
10.7%
a 145
7.8%
t 144
7.7%
c 137
7.3%
o 120
 
6.4%
n 115
 
6.2%
r 113
 
6.1%
d 101
 
5.4%
Other values (8) 335
18.0%
Uppercase Letter
ValueCountFrequency (%)
S 134
39.6%
M 44
 
13.0%
C 42
 
12.4%
E 41
 
12.1%
G 41
 
12.1%
D 9
 
2.7%
V 9
 
2.7%
I 9
 
2.7%
A 5
 
1.5%
T 2
 
0.6%
Other values (2) 2
 
0.6%
Decimal Number
ValueCountFrequency (%)
0 322
43.3%
1 150
20.2%
5 95
 
12.8%
7 49
 
6.6%
6 46
 
6.2%
8 45
 
6.0%
3 13
 
1.7%
9 9
 
1.2%
2 8
 
1.1%
4 7
 
0.9%
Other Punctuation
ValueCountFrequency (%)
, 123
67.6%
: 53
29.1%
. 6
 
3.3%
Space Separator
ValueCountFrequency (%)
443
100.0%
Close Punctuation
ValueCountFrequency (%)
) 149
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 149
100.0%
Open Punctuation
ValueCountFrequency (%)
( 149
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2202
54.8%
Common 1816
45.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 255
 
11.6%
i 200
 
9.1%
s 199
 
9.0%
a 145
 
6.6%
t 144
 
6.5%
c 137
 
6.2%
S 134
 
6.1%
o 120
 
5.4%
n 115
 
5.2%
r 113
 
5.1%
Other values (20) 640
29.1%
Common
ValueCountFrequency (%)
443
24.4%
0 322
17.7%
1 150
 
8.3%
) 149
 
8.2%
- 149
 
8.2%
( 149
 
8.2%
, 123
 
6.8%
5 95
 
5.2%
: 53
 
2.9%
7 49
 
2.7%
Other values (7) 134
 
7.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4018
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
443
 
11.0%
0 322
 
8.0%
e 255
 
6.3%
i 200
 
5.0%
s 199
 
5.0%
1 150
 
3.7%
) 149
 
3.7%
- 149
 
3.7%
( 149
 
3.7%
a 145
 
3.6%
Other values (37) 1857
46.2%

requirement1_3
Text

MISSING 

Distinct34
Distinct (%)79.1%
Missing397
Missing (%)90.2%
Memory size17.9 KiB
2023-12-09T22:07:21.364453image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length89
Median length89
Mean length70.6744186
Min length8

Characters and Unicode

Total characters3039
Distinct characters44
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique30 ?
Unique (%)69.8%

Sample

1st rowCourse Grades: English (75-100), Math (70-100), Social Studies (78-100), Science (80-100)
2nd rowCourse Grades: English (74-100), Math (68-100), Social Studies (67-100), Science (73-100)
3rd rowCourse Grades: English (60-100), Math (65-100), Social Studies (56-100), Science (55-100)
4th rowCourse Grades: English (69-100), Math (65-100), Social Studies (65-100), Science (65-100)
5th rowCourse Grades: English, Math, Social Studies, Science
ValueCountFrequency (%)
course 34
 
9.0%
math 34
 
9.0%
grades 34
 
9.0%
english 33
 
8.8%
science 32
 
8.5%
social 30
 
8.0%
studies 30
 
8.0%
55-100 24
 
6.4%
65-100 23
 
6.1%
75-100 10
 
2.7%
Other values (37) 92
24.5%
2023-12-09T22:07:21.779238image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
333
 
11.0%
0 258
 
8.5%
e 186
 
6.1%
s 149
 
4.9%
i 143
 
4.7%
) 121
 
4.0%
1 121
 
4.0%
- 121
 
4.0%
( 121
 
4.0%
a 107
 
3.5%
Other values (34) 1379
45.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1348
44.4%
Decimal Number 603
19.8%
Space Separator 333
 
11.0%
Uppercase Letter 254
 
8.4%
Other Punctuation 138
 
4.5%
Close Punctuation 121
 
4.0%
Dash Punctuation 121
 
4.0%
Open Punctuation 121
 
4.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 186
13.8%
s 149
11.1%
i 143
10.6%
a 107
7.9%
c 100
7.4%
t 95
 
7.0%
o 83
 
6.2%
r 81
 
6.0%
n 80
 
5.9%
d 75
 
5.6%
Other values (6) 249
18.5%
Uppercase Letter
ValueCountFrequency (%)
S 99
39.0%
C 34
 
13.4%
M 34
 
13.4%
G 34
 
13.4%
E 33
 
13.0%
D 5
 
2.0%
V 5
 
2.0%
A 4
 
1.6%
I 4
 
1.6%
T 1
 
0.4%
Decimal Number
ValueCountFrequency (%)
0 258
42.8%
1 121
20.1%
5 87
 
14.4%
6 48
 
8.0%
7 36
 
6.0%
8 24
 
4.0%
9 13
 
2.2%
4 6
 
1.0%
2 6
 
1.0%
3 4
 
0.7%
Other Punctuation
ValueCountFrequency (%)
, 94
68.1%
: 40
29.0%
. 4
 
2.9%
Space Separator
ValueCountFrequency (%)
333
100.0%
Close Punctuation
ValueCountFrequency (%)
) 121
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 121
100.0%
Open Punctuation
ValueCountFrequency (%)
( 121
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1602
52.7%
Common 1437
47.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 186
 
11.6%
s 149
 
9.3%
i 143
 
8.9%
a 107
 
6.7%
c 100
 
6.2%
S 99
 
6.2%
t 95
 
5.9%
o 83
 
5.2%
r 81
 
5.1%
n 80
 
5.0%
Other values (17) 479
29.9%
Common
ValueCountFrequency (%)
333
23.2%
0 258
18.0%
) 121
 
8.4%
1 121
 
8.4%
- 121
 
8.4%
( 121
 
8.4%
, 94
 
6.5%
5 87
 
6.1%
6 48
 
3.3%
: 40
 
2.8%
Other values (7) 93
 
6.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3039
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
333
 
11.0%
0 258
 
8.5%
e 186
 
6.1%
s 149
 
4.9%
i 143
 
4.7%
) 121
 
4.0%
1 121
 
4.0%
- 121
 
4.0%
( 121
 
4.0%
a 107
 
3.5%
Other values (34) 1379
45.4%

requirement1_4
Text

MISSING 

Distinct30
Distinct (%)85.7%
Missing405
Missing (%)92.0%
Memory size17.2 KiB
2023-12-09T22:07:22.028883image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length89
Median length89
Mean length73.48571429
Min length8

Characters and Unicode

Total characters2572
Distinct characters40
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique26 ?
Unique (%)74.3%

Sample

1st rowCourse Grades: English (77-100), Math (80-100), Social Studies (70-100), Science (80-100)
2nd rowCourse Grades: English (77-100), Math (79-100), Social Studies (76-100), Science (73-100)
3rd rowCourse Grades: English, Math, Social Studies, Science
4th rowCourse Grades: English (65-100), Math (67-100), Social Studies (70-100), Science (68-100)
5th rowCourse Grades: English (65-100), Math (65-100), Science (65-100), Social Studies (65-100)
ValueCountFrequency (%)
course 29
9.1%
grades 29
9.1%
english 28
8.8%
math 28
8.8%
social 28
8.8%
studies 28
8.8%
science 28
8.8%
65-100 24
 
7.5%
55-100 16
 
5.0%
70-100 13
 
4.1%
Other values (29) 68
21.3%
2023-12-09T22:07:22.431587image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
284
 
11.0%
0 225
 
8.7%
e 159
 
6.2%
i 126
 
4.9%
s 126
 
4.9%
1 101
 
3.9%
- 100
 
3.9%
) 100
 
3.9%
( 100
 
3.9%
a 90
 
3.5%
Other values (30) 1161
45.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1155
44.9%
Decimal Number 500
19.4%
Space Separator 284
 
11.0%
Uppercase Letter 217
 
8.4%
Other Punctuation 116
 
4.5%
Dash Punctuation 100
 
3.9%
Close Punctuation 100
 
3.9%
Open Punctuation 100
 
3.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 159
13.8%
i 126
10.9%
s 126
10.9%
a 90
7.8%
c 89
7.7%
t 82
 
7.1%
o 73
 
6.3%
n 68
 
5.9%
r 68
 
5.9%
d 63
 
5.5%
Other values (5) 211
18.3%
Uppercase Letter
ValueCountFrequency (%)
S 88
40.6%
C 30
 
13.8%
G 29
 
13.4%
M 28
 
12.9%
E 28
 
12.9%
V 4
 
1.8%
D 4
 
1.8%
I 3
 
1.4%
A 2
 
0.9%
W 1
 
0.5%
Decimal Number
ValueCountFrequency (%)
0 225
45.0%
1 101
20.2%
5 64
 
12.8%
6 43
 
8.6%
7 32
 
6.4%
8 20
 
4.0%
9 9
 
1.8%
3 4
 
0.8%
4 2
 
0.4%
Other Punctuation
ValueCountFrequency (%)
, 83
71.6%
: 33
 
28.4%
Space Separator
ValueCountFrequency (%)
284
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 100
100.0%
Close Punctuation
ValueCountFrequency (%)
) 100
100.0%
Open Punctuation
ValueCountFrequency (%)
( 100
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1372
53.3%
Common 1200
46.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 159
 
11.6%
i 126
 
9.2%
s 126
 
9.2%
a 90
 
6.6%
c 89
 
6.5%
S 88
 
6.4%
t 82
 
6.0%
o 73
 
5.3%
n 68
 
5.0%
r 68
 
5.0%
Other values (15) 403
29.4%
Common
ValueCountFrequency (%)
284
23.7%
0 225
18.8%
1 101
 
8.4%
- 100
 
8.3%
) 100
 
8.3%
( 100
 
8.3%
, 83
 
6.9%
5 64
 
5.3%
6 43
 
3.6%
: 33
 
2.8%
Other values (5) 67
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2572
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
284
 
11.0%
0 225
 
8.7%
e 159
 
6.2%
i 126
 
4.9%
s 126
 
4.9%
1 101
 
3.9%
- 100
 
3.9%
) 100
 
3.9%
( 100
 
3.9%
a 90
 
3.5%
Other values (30) 1161
45.1%

requirement1_5
Text

MISSING 

Distinct16
Distinct (%)69.6%
Missing417
Missing (%)94.8%
Memory size15.9 KiB
2023-12-09T22:07:22.668789image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length89
Median length89
Mean length64.73913043
Min length8

Characters and Unicode

Total characters1489
Distinct characters40
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique13 ?
Unique (%)56.5%

Sample

1st rowCourse Grades: English (80-100), Math (78-100), Social Studies (75-100), Science (75-100)
2nd rowCourse Grades: English (55-100), Math (55-100), Social Studies (55-100), Science (55-100)
3rd rowCourse Grades: English (55-100), Math (55-100), Social Studies (55-100), Science (55-100)
4th rowAttendance and Punctuality
5th rowAudition
ValueCountFrequency (%)
55-100 19
10.4%
course 15
 
8.2%
english 15
 
8.2%
math 15
 
8.2%
social 15
 
8.2%
studies 15
 
8.2%
science 15
 
8.2%
grades 15
 
8.2%
70-100 10
 
5.5%
65-100 8
 
4.4%
Other values (18) 41
22.4%
2023-12-09T22:07:23.048258image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
160
 
10.7%
0 126
 
8.5%
e 93
 
6.2%
i 76
 
5.1%
s 72
 
4.8%
1 58
 
3.9%
t 57
 
3.8%
) 56
 
3.8%
- 56
 
3.8%
( 56
 
3.8%
Other values (30) 679
45.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 692
46.5%
Decimal Number 280
18.8%
Space Separator 160
 
10.7%
Uppercase Letter 125
 
8.4%
Other Punctuation 64
 
4.3%
Close Punctuation 56
 
3.8%
Dash Punctuation 56
 
3.8%
Open Punctuation 56
 
3.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 93
13.4%
i 76
11.0%
s 72
10.4%
t 57
8.2%
a 52
7.5%
c 51
7.4%
o 45
 
6.5%
n 45
 
6.5%
d 39
 
5.6%
r 38
 
5.5%
Other values (6) 124
17.9%
Uppercase Letter
ValueCountFrequency (%)
S 49
39.2%
C 15
 
12.0%
M 15
 
12.0%
E 15
 
12.0%
G 15
 
12.0%
A 4
 
3.2%
D 4
 
3.2%
V 4
 
3.2%
I 3
 
2.4%
P 1
 
0.8%
Decimal Number
ValueCountFrequency (%)
0 126
45.0%
1 58
20.7%
5 53
18.9%
7 19
 
6.8%
8 11
 
3.9%
6 11
 
3.9%
2 1
 
0.4%
4 1
 
0.4%
Other Punctuation
ValueCountFrequency (%)
, 45
70.3%
: 19
29.7%
Space Separator
ValueCountFrequency (%)
160
100.0%
Close Punctuation
ValueCountFrequency (%)
) 56
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 56
100.0%
Open Punctuation
ValueCountFrequency (%)
( 56
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 817
54.9%
Common 672
45.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 93
 
11.4%
i 76
 
9.3%
s 72
 
8.8%
t 57
 
7.0%
a 52
 
6.4%
c 51
 
6.2%
S 49
 
6.0%
o 45
 
5.5%
n 45
 
5.5%
d 39
 
4.8%
Other values (16) 238
29.1%
Common
ValueCountFrequency (%)
160
23.8%
0 126
18.8%
1 58
 
8.6%
) 56
 
8.3%
- 56
 
8.3%
( 56
 
8.3%
5 53
 
7.9%
, 45
 
6.7%
: 19
 
2.8%
7 19
 
2.8%
Other values (4) 24
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1489
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
160
 
10.7%
0 126
 
8.5%
e 93
 
6.2%
i 76
 
5.1%
s 72
 
4.8%
1 58
 
3.9%
t 57
 
3.8%
) 56
 
3.8%
- 56
 
3.8%
( 56
 
3.8%
Other values (30) 679
45.6%

requirement1_6
Text

MISSING 

Distinct11
Distinct (%)78.6%
Missing426
Missing (%)96.8%
Memory size15.1 KiB
2023-12-09T22:07:23.292340image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length89
Median length89
Mean length63.92857143
Min length8

Characters and Unicode

Total characters895
Distinct characters39
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10 ?
Unique (%)71.4%

Sample

1st rowCourse Grades: English (86-100), Math (81-100), Social Studies (83-100), Science (81-100)
2nd rowCourse Grades: English (60-100), Math (60-100), Social Studies (63-100), Science (58-100)
3rd rowCourse Grades: English (58-100), Math (55-100), Social Studies (60-100), Science (64-100)
4th rowDemonstrated Interest: School Visit
5th rowCourse Grades: English (70-100), Math (65-100), Social Studies (65-100), Science (65-100)
ValueCountFrequency (%)
math 8
 
7.3%
social 8
 
7.3%
science 8
 
7.3%
course 8
 
7.3%
grades 8
 
7.3%
english 8
 
7.3%
studies 8
 
7.3%
interest 5
 
4.6%
demonstrated 5
 
4.6%
visit 5
 
4.6%
Other values (20) 38
34.9%
2023-12-09T22:07:23.664644image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
95
 
10.6%
0 72
 
8.0%
e 60
 
6.7%
s 47
 
5.3%
i 45
 
5.0%
t 42
 
4.7%
1 34
 
3.8%
( 32
 
3.6%
- 32
 
3.6%
) 32
 
3.6%
Other values (29) 404
45.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 431
48.2%
Decimal Number 160
 
17.9%
Space Separator 95
 
10.6%
Uppercase Letter 76
 
8.5%
Other Punctuation 37
 
4.1%
Open Punctuation 32
 
3.6%
Dash Punctuation 32
 
3.6%
Close Punctuation 32
 
3.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 60
13.9%
s 47
10.9%
i 45
10.4%
t 42
9.7%
o 32
7.4%
a 29
6.7%
c 29
6.7%
n 27
 
6.3%
r 26
 
6.0%
d 22
 
5.1%
Other values (5) 72
16.7%
Decimal Number
ValueCountFrequency (%)
0 72
45.0%
1 34
21.2%
5 14
 
8.8%
8 13
 
8.1%
6 12
 
7.5%
7 9
 
5.6%
3 3
 
1.9%
2 2
 
1.2%
4 1
 
0.6%
Uppercase Letter
ValueCountFrequency (%)
S 29
38.2%
M 8
 
10.5%
G 8
 
10.5%
E 8
 
10.5%
C 8
 
10.5%
D 5
 
6.6%
V 5
 
6.6%
I 4
 
5.3%
A 1
 
1.3%
Other Punctuation
ValueCountFrequency (%)
, 24
64.9%
: 13
35.1%
Space Separator
ValueCountFrequency (%)
95
100.0%
Open Punctuation
ValueCountFrequency (%)
( 32
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 32
100.0%
Close Punctuation
ValueCountFrequency (%)
) 32
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 507
56.6%
Common 388
43.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 60
11.8%
s 47
 
9.3%
i 45
 
8.9%
t 42
 
8.3%
o 32
 
6.3%
a 29
 
5.7%
S 29
 
5.7%
c 29
 
5.7%
n 27
 
5.3%
r 26
 
5.1%
Other values (14) 141
27.8%
Common
ValueCountFrequency (%)
95
24.5%
0 72
18.6%
1 34
 
8.8%
( 32
 
8.2%
- 32
 
8.2%
) 32
 
8.2%
, 24
 
6.2%
5 14
 
3.6%
: 13
 
3.4%
8 13
 
3.4%
Other values (5) 27
 
7.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 895
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
95
 
10.6%
0 72
 
8.0%
e 60
 
6.7%
s 47
 
5.3%
i 45
 
5.0%
t 42
 
4.7%
1 34
 
3.8%
( 32
 
3.6%
- 32
 
3.6%
) 32
 
3.6%
Other values (29) 404
45.1%

requirement1_7
Text

MISSING 

Distinct7
Distinct (%)100.0%
Missing433
Missing (%)98.4%
Memory size14.5 KiB
2023-12-09T22:07:23.886924image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length89
Median length89
Mean length63.14285714
Min length8

Characters and Unicode

Total characters442
Distinct characters34
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7 ?
Unique (%)100.0%

Sample

1st rowTest (on-site)
2nd rowCourse Grades: English (60-100), Math (55-100), Social Studies (61-100), Science (65-100)
3rd rowCourse Grades: English (80-100), Math (80-100), Social Studies (85-100), Science (80-100)
4th rowAudition
5th rowCourse Grades: English (80-100), Math (75-100), Social Studies (75-100), Science (75-100)
ValueCountFrequency (%)
course 5
9.1%
science 5
9.1%
english 5
9.1%
math 5
9.1%
80-100 5
9.1%
grades 5
9.1%
social 4
 
7.3%
studies 4
 
7.3%
75-100 3
 
5.5%
85-100 3
 
5.5%
Other values (11) 11
20.0%
2023-12-09T22:07:24.242421image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
48
 
10.9%
0 44
 
10.0%
e 26
 
5.9%
s 21
 
4.8%
1 21
 
4.8%
i 21
 
4.8%
( 20
 
4.5%
) 20
 
4.5%
- 20
 
4.5%
c 14
 
3.2%
Other values (24) 187
42.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 185
41.9%
Decimal Number 95
21.5%
Space Separator 48
 
10.9%
Uppercase Letter 35
 
7.9%
Open Punctuation 20
 
4.5%
Close Punctuation 20
 
4.5%
Dash Punctuation 20
 
4.5%
Other Punctuation 19
 
4.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 26
14.1%
s 21
11.4%
i 21
11.4%
c 14
7.6%
a 14
7.6%
t 12
 
6.5%
n 12
 
6.5%
o 11
 
5.9%
d 10
 
5.4%
h 10
 
5.4%
Other values (4) 34
18.4%
Decimal Number
ValueCountFrequency (%)
0 44
46.3%
1 21
22.1%
8 13
 
13.7%
5 9
 
9.5%
7 4
 
4.2%
6 3
 
3.2%
2 1
 
1.1%
Uppercase Letter
ValueCountFrequency (%)
S 13
37.1%
M 5
 
14.3%
C 5
 
14.3%
E 5
 
14.3%
G 5
 
14.3%
A 1
 
2.9%
T 1
 
2.9%
Other Punctuation
ValueCountFrequency (%)
, 14
73.7%
: 5
 
26.3%
Space Separator
ValueCountFrequency (%)
48
100.0%
Open Punctuation
ValueCountFrequency (%)
( 20
100.0%
Close Punctuation
ValueCountFrequency (%)
) 20
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 20
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 222
50.2%
Latin 220
49.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 26
 
11.8%
s 21
 
9.5%
i 21
 
9.5%
c 14
 
6.4%
a 14
 
6.4%
S 13
 
5.9%
t 12
 
5.5%
n 12
 
5.5%
o 11
 
5.0%
d 10
 
4.5%
Other values (11) 66
30.0%
Common
ValueCountFrequency (%)
48
21.6%
0 44
19.8%
1 21
9.5%
( 20
9.0%
) 20
9.0%
- 20
9.0%
, 14
 
6.3%
8 13
 
5.9%
5 9
 
4.1%
: 5
 
2.3%
Other values (3) 8
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 442
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
48
 
10.9%
0 44
 
10.0%
e 26
 
5.9%
s 21
 
4.8%
1 21
 
4.8%
i 21
 
4.8%
( 20
 
4.5%
) 20
 
4.5%
- 20
 
4.5%
c 14
 
3.2%
Other values (24) 187
42.3%

requirement1_8
Text

MISSING 

Distinct2
Distinct (%)100.0%
Missing438
Missing (%)99.5%
Memory size14.0 KiB
2023-12-09T22:07:24.437849image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length89
Median length62
Mean length62
Min length35

Characters and Unicode

Total characters124
Distinct characters34
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st rowCourse Grades: English (60-100), Math (65-100), Social Studies (65-100), Science (70-100)
2nd rowDemonstrated Interest: School Visit
ValueCountFrequency (%)
65-100 2
13.3%
course 1
 
6.7%
grades 1
 
6.7%
english 1
 
6.7%
60-100 1
 
6.7%
math 1
 
6.7%
social 1
 
6.7%
studies 1
 
6.7%
science 1
 
6.7%
70-100 1
 
6.7%
Other values (4) 4
26.7%
2023-12-09T22:07:24.751589image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
13
 
10.5%
0 10
 
8.1%
e 9
 
7.3%
t 7
 
5.6%
s 7
 
5.6%
i 6
 
4.8%
o 5
 
4.0%
( 4
 
3.2%
c 4
 
3.2%
) 4
 
3.2%
Other values (24) 55
44.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 63
50.8%
Decimal Number 20
 
16.1%
Space Separator 13
 
10.5%
Uppercase Letter 11
 
8.9%
Other Punctuation 5
 
4.0%
Open Punctuation 4
 
3.2%
Close Punctuation 4
 
3.2%
Dash Punctuation 4
 
3.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 9
14.3%
t 7
11.1%
s 7
11.1%
i 6
9.5%
o 5
7.9%
c 4
 
6.3%
n 4
 
6.3%
a 4
 
6.3%
r 4
 
6.3%
h 3
 
4.8%
Other values (5) 10
15.9%
Uppercase Letter
ValueCountFrequency (%)
S 4
36.4%
D 1
 
9.1%
I 1
 
9.1%
C 1
 
9.1%
M 1
 
9.1%
E 1
 
9.1%
G 1
 
9.1%
V 1
 
9.1%
Decimal Number
ValueCountFrequency (%)
0 10
50.0%
1 4
 
20.0%
6 3
 
15.0%
5 2
 
10.0%
7 1
 
5.0%
Other Punctuation
ValueCountFrequency (%)
, 3
60.0%
: 2
40.0%
Space Separator
ValueCountFrequency (%)
13
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 74
59.7%
Common 50
40.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 9
12.2%
t 7
 
9.5%
s 7
 
9.5%
i 6
 
8.1%
o 5
 
6.8%
c 4
 
5.4%
S 4
 
5.4%
n 4
 
5.4%
a 4
 
5.4%
r 4
 
5.4%
Other values (13) 20
27.0%
Common
ValueCountFrequency (%)
13
26.0%
0 10
20.0%
( 4
 
8.0%
) 4
 
8.0%
1 4
 
8.0%
- 4
 
8.0%
6 3
 
6.0%
, 3
 
6.0%
: 2
 
4.0%
5 2
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 124
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
13
 
10.5%
0 10
 
8.1%
e 9
 
7.3%
t 7
 
5.6%
s 7
 
5.6%
i 6
 
4.8%
o 5
 
4.0%
( 4
 
3.2%
c 4
 
3.2%
) 4
 
3.2%
Other values (24) 55
44.4%

requirement1_9
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing440
Missing (%)100.0%
Memory size3.6 KiB

requirement1_10
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing440
Missing (%)100.0%
Memory size3.6 KiB

requirement2_1
Text

MISSING 

Distinct53
Distinct (%)53.0%
Missing340
Missing (%)77.3%
Memory size22.3 KiB
2023-12-09T22:07:24.993232image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length89
Median length73
Mean length61.38
Min length9

Characters and Unicode

Total characters6138
Distinct characters52
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique38 ?
Unique (%)38.0%

Sample

1st rowStandardized Test Scores: English Language Arts (2.8-4.5), Math (2.8-4.5)
2nd rowInterview
3rd rowStandardized Test Scores: English Language Arts (2.0-4.5), Math (2.0-4.5)
4th rowStandardized Test Scores: English Language Arts (2.1-4.5), Math (2.1-4.5)
5th rowAttendance and Punctuality
ValueCountFrequency (%)
math 80
10.6%
english 79
10.4%
standardized 76
10.0%
arts 76
10.0%
test 76
10.0%
language 76
10.0%
scores 76
10.0%
2.0-4.5 28
 
3.7%
1.9-4.5 25
 
3.3%
1.8-4.5 17
 
2.2%
Other values (49) 148
19.6%
2023-12-09T22:07:25.384970image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
657
 
10.7%
a 421
 
6.9%
t 373
 
6.1%
e 364
 
5.9%
s 327
 
5.3%
n 288
 
4.7%
. 280
 
4.6%
d 257
 
4.2%
r 246
 
4.0%
g 232
 
3.8%
Other values (42) 2693
43.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 3358
54.7%
Space Separator 657
 
10.7%
Decimal Number 620
 
10.1%
Uppercase Letter 598
 
9.7%
Other Punctuation 446
 
7.3%
Close Punctuation 153
 
2.5%
Open Punctuation 153
 
2.5%
Dash Punctuation 153
 
2.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 421
12.5%
t 373
11.1%
e 364
10.8%
s 327
9.7%
n 288
8.6%
d 257
7.7%
r 246
7.3%
g 232
6.9%
i 191
 
5.7%
h 163
 
4.9%
Other values (11) 496
14.8%
Uppercase Letter
ValueCountFrequency (%)
S 165
27.6%
A 90
15.1%
E 81
13.5%
M 80
13.4%
T 76
12.7%
L 76
12.7%
P 8
 
1.3%
I 5
 
0.8%
C 4
 
0.7%
G 4
 
0.7%
Other values (4) 9
 
1.5%
Decimal Number
ValueCountFrequency (%)
5 151
24.4%
4 142
22.9%
2 78
12.6%
1 73
11.8%
0 56
 
9.0%
9 30
 
4.8%
3 29
 
4.7%
8 25
 
4.0%
6 18
 
2.9%
7 18
 
2.9%
Other Punctuation
ValueCountFrequency (%)
. 280
62.8%
, 85
 
19.1%
: 81
 
18.2%
Space Separator
ValueCountFrequency (%)
657
100.0%
Close Punctuation
ValueCountFrequency (%)
) 153
100.0%
Open Punctuation
ValueCountFrequency (%)
( 153
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 153
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 3956
64.5%
Common 2182
35.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 421
 
10.6%
t 373
 
9.4%
e 364
 
9.2%
s 327
 
8.3%
n 288
 
7.3%
d 257
 
6.5%
r 246
 
6.2%
g 232
 
5.9%
i 191
 
4.8%
S 165
 
4.2%
Other values (25) 1092
27.6%
Common
ValueCountFrequency (%)
657
30.1%
. 280
12.8%
) 153
 
7.0%
( 153
 
7.0%
- 153
 
7.0%
5 151
 
6.9%
4 142
 
6.5%
, 85
 
3.9%
: 81
 
3.7%
2 78
 
3.6%
Other values (7) 249
 
11.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6138
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
657
 
10.7%
a 421
 
6.9%
t 373
 
6.1%
e 364
 
5.9%
s 327
 
5.3%
n 288
 
4.7%
. 280
 
4.6%
d 257
 
4.2%
r 246
 
4.0%
g 232
 
3.8%
Other values (42) 2693
43.9%

requirement2_2
Text

MISSING 

Distinct31
Distinct (%)68.9%
Missing395
Missing (%)89.8%
Memory size17.8 KiB
2023-12-09T22:07:25.631663image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length89
Median length73
Mean length65.02222222
Min length10

Characters and Unicode

Total characters2926
Distinct characters44
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique21 ?
Unique (%)46.7%

Sample

1st rowStandardized Test Scores: Math (1.7-4.5)
2nd rowStandardized Test Scores: English Language Arts (2.4-4.5), Math (2.2-4.5)
3rd rowStandardized Test Scores: English Language Arts (2.3-4.5), Math (2.0-4.5)
4th rowStandardized Test Scores: English Language Arts (2.0-4.5), Math (1.9-4.5)
5th rowStandardized Test Scores: English Language Arts (2.1-4.5), Math (2.2-4.5)
ValueCountFrequency (%)
english 39
10.7%
math 39
10.7%
standardized 38
10.5%
test 38
10.5%
scores 38
10.5%
language 38
10.5%
arts 37
10.2%
1.9-4.5 13
 
3.6%
1.8-4.5 12
 
3.3%
2.0-4.5 8
 
2.2%
Other values (31) 63
17.4%
2023-12-09T22:07:26.017785image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
318
 
10.9%
a 206
 
7.0%
t 173
 
5.9%
e 169
 
5.8%
s 156
 
5.3%
. 138
 
4.7%
n 133
 
4.5%
d 124
 
4.2%
r 119
 
4.1%
g 115
 
3.9%
Other values (34) 1275
43.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1588
54.3%
Space Separator 318
 
10.9%
Decimal Number 296
 
10.1%
Uppercase Letter 287
 
9.8%
Other Punctuation 218
 
7.5%
Close Punctuation 73
 
2.5%
Dash Punctuation 73
 
2.5%
Open Punctuation 73
 
2.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 206
13.0%
t 173
10.9%
e 169
10.6%
s 156
9.8%
n 133
8.4%
d 124
7.8%
r 119
7.5%
g 115
7.2%
i 85
 
5.4%
h 82
 
5.2%
Other values (6) 226
14.2%
Uppercase Letter
ValueCountFrequency (%)
S 80
27.9%
A 41
14.3%
T 39
13.6%
E 39
13.6%
M 39
13.6%
L 38
13.2%
P 3
 
1.0%
C 3
 
1.0%
G 2
 
0.7%
W 2
 
0.7%
Decimal Number
ValueCountFrequency (%)
5 81
27.4%
4 70
23.6%
1 46
15.5%
2 28
 
9.5%
0 19
 
6.4%
8 15
 
5.1%
9 14
 
4.7%
3 11
 
3.7%
6 6
 
2.0%
7 6
 
2.0%
Other Punctuation
ValueCountFrequency (%)
. 138
63.3%
, 40
 
18.3%
: 40
 
18.3%
Space Separator
ValueCountFrequency (%)
318
100.0%
Close Punctuation
ValueCountFrequency (%)
) 73
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 73
100.0%
Open Punctuation
ValueCountFrequency (%)
( 73
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1875
64.1%
Common 1051
35.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 206
11.0%
t 173
 
9.2%
e 169
 
9.0%
s 156
 
8.3%
n 133
 
7.1%
d 124
 
6.6%
r 119
 
6.3%
g 115
 
6.1%
i 85
 
4.5%
h 82
 
4.4%
Other values (17) 513
27.4%
Common
ValueCountFrequency (%)
318
30.3%
. 138
13.1%
5 81
 
7.7%
) 73
 
6.9%
- 73
 
6.9%
( 73
 
6.9%
4 70
 
6.7%
1 46
 
4.4%
, 40
 
3.8%
: 40
 
3.8%
Other values (7) 99
 
9.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2926
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
318
 
10.9%
a 206
 
7.0%
t 173
 
5.9%
e 169
 
5.8%
s 156
 
5.3%
. 138
 
4.7%
n 133
 
4.5%
d 124
 
4.2%
r 119
 
4.1%
g 115
 
3.9%
Other values (34) 1275
43.6%

requirement2_3
Text

MISSING 

Distinct23
Distinct (%)65.7%
Missing405
Missing (%)92.0%
Memory size17.0 KiB
2023-12-09T22:07:26.246968image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length73
Median length73
Mean length67.02857143
Min length10

Characters and Unicode

Total characters2346
Distinct characters42
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique17 ?
Unique (%)48.6%

Sample

1st rowStandardized Test Scores: English Language Arts (2.0-4.5), Math (2.4-4.5)
2nd rowStandardized Test Scores: English Language Arts (1.8-4.5), Math (2.0-4.5)
3rd rowStandardized Test Scores: English Language Arts (1.8-4.5), Math (1.5-4.5)
4th rowStandardized Test Scores: English Language Arts (1.9-4.5), Math (1.8-4.5)
5th rowAttendance and Punctuality
ValueCountFrequency (%)
english 32
11.0%
language 32
11.0%
standardized 31
10.7%
test 31
10.7%
scores 31
10.7%
arts 31
10.7%
math 31
10.7%
1.8-4.5 15
5.2%
1.9-4.5 14
 
4.8%
1.7-4.5 5
 
1.7%
Other values (20) 37
12.8%
2023-12-09T22:07:26.610909image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
255
 
10.9%
a 166
 
7.1%
t 135
 
5.8%
e 134
 
5.7%
s 126
 
5.4%
. 120
 
5.1%
n 106
 
4.5%
d 99
 
4.2%
r 96
 
4.1%
g 96
 
4.1%
Other values (32) 1013
43.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1260
53.7%
Space Separator 255
 
10.9%
Decimal Number 240
 
10.2%
Uppercase Letter 228
 
9.7%
Other Punctuation 183
 
7.8%
Dash Punctuation 60
 
2.6%
Close Punctuation 60
 
2.6%
Open Punctuation 60
 
2.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 166
13.2%
t 135
10.7%
e 134
10.6%
s 126
10.0%
n 106
8.4%
d 99
7.9%
r 96
7.6%
g 96
7.6%
i 65
 
5.2%
h 65
 
5.2%
Other values (6) 172
13.7%
Uppercase Letter
ValueCountFrequency (%)
S 62
27.2%
A 34
14.9%
L 32
14.0%
E 32
14.0%
T 32
14.0%
M 31
13.6%
P 2
 
0.9%
C 1
 
0.4%
G 1
 
0.4%
O 1
 
0.4%
Decimal Number
ValueCountFrequency (%)
5 66
27.5%
4 62
25.8%
1 43
17.9%
8 20
 
8.3%
2 17
 
7.1%
9 14
 
5.8%
3 8
 
3.3%
7 6
 
2.5%
0 4
 
1.7%
Other Punctuation
ValueCountFrequency (%)
. 120
65.6%
: 32
 
17.5%
, 31
 
16.9%
Space Separator
ValueCountFrequency (%)
255
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 60
100.0%
Close Punctuation
ValueCountFrequency (%)
) 60
100.0%
Open Punctuation
ValueCountFrequency (%)
( 60
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1488
63.4%
Common 858
36.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 166
11.2%
t 135
 
9.1%
e 134
 
9.0%
s 126
 
8.5%
n 106
 
7.1%
d 99
 
6.7%
r 96
 
6.5%
g 96
 
6.5%
i 65
 
4.4%
h 65
 
4.4%
Other values (16) 400
26.9%
Common
ValueCountFrequency (%)
255
29.7%
. 120
14.0%
5 66
 
7.7%
4 62
 
7.2%
- 60
 
7.0%
) 60
 
7.0%
( 60
 
7.0%
1 43
 
5.0%
: 32
 
3.7%
, 31
 
3.6%
Other values (6) 69
 
8.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2346
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
255
 
10.9%
a 166
 
7.1%
t 135
 
5.8%
e 134
 
5.7%
s 126
 
5.4%
. 120
 
5.1%
n 106
 
4.5%
d 99
 
4.2%
r 96
 
4.1%
g 96
 
4.1%
Other values (32) 1013
43.2%

requirement2_4
Text

MISSING 

Distinct21
Distinct (%)72.4%
Missing411
Missing (%)93.4%
Memory size16.5 KiB
2023-12-09T22:07:26.826796image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length73
Median length73
Mean length66.51724138
Min length8

Characters and Unicode

Total characters1929
Distinct characters38
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique17 ?
Unique (%)58.6%

Sample

1st rowStandardized Test Scores: English Language Arts (2.2-4.5), Math (2.6-4.5)
2nd rowStandardized Test Scores: English Language Arts (2.0-4.5), Math (2.1-4.5)
3rd rowStandardized Test Scores: English Language Arts, Math
4th rowStandardized Test Scores: English Language Arts (1.9-4.5), Math (1.9-4.5)
5th rowStandardized Test Scores: English Language Arts (1.9-4.5), Math (1.9-4.5)
ValueCountFrequency (%)
standardized 27
11.3%
test 27
11.3%
scores 27
11.3%
english 27
11.3%
language 27
11.3%
arts 27
11.3%
math 27
11.3%
1.9-4.5 15
6.3%
1.8-4.5 8
 
3.3%
1.7-4.5 6
 
2.5%
Other values (13) 21
8.8%
2023-12-09T22:07:27.169172image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
210
 
10.9%
a 136
 
7.1%
t 111
 
5.8%
e 110
 
5.7%
s 108
 
5.6%
. 96
 
5.0%
n 84
 
4.4%
d 83
 
4.3%
g 81
 
4.2%
r 81
 
4.2%
Other values (28) 829
43.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1042
54.0%
Space Separator 210
 
10.9%
Decimal Number 192
 
10.0%
Uppercase Letter 191
 
9.9%
Other Punctuation 150
 
7.8%
Close Punctuation 48
 
2.5%
Dash Punctuation 48
 
2.5%
Open Punctuation 48
 
2.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 136
13.1%
t 111
10.7%
e 110
10.6%
s 108
10.4%
n 84
8.1%
d 83
8.0%
g 81
7.8%
r 81
7.8%
i 56
5.4%
h 54
 
5.2%
Other values (5) 138
13.2%
Decimal Number
ValueCountFrequency (%)
5 49
25.5%
4 48
25.0%
1 35
18.2%
9 15
 
7.8%
2 15
 
7.8%
8 8
 
4.2%
7 7
 
3.6%
3 7
 
3.6%
0 5
 
2.6%
6 3
 
1.6%
Uppercase Letter
ValueCountFrequency (%)
S 54
28.3%
A 29
15.2%
M 27
14.1%
L 27
14.1%
E 27
14.1%
T 27
14.1%
Other Punctuation
ValueCountFrequency (%)
. 96
64.0%
, 27
 
18.0%
: 27
 
18.0%
Space Separator
ValueCountFrequency (%)
210
100.0%
Close Punctuation
ValueCountFrequency (%)
) 48
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 48
100.0%
Open Punctuation
ValueCountFrequency (%)
( 48
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1233
63.9%
Common 696
36.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 136
11.0%
t 111
 
9.0%
e 110
 
8.9%
s 108
 
8.8%
n 84
 
6.8%
d 83
 
6.7%
g 81
 
6.6%
r 81
 
6.6%
i 56
 
4.5%
h 54
 
4.4%
Other values (11) 329
26.7%
Common
ValueCountFrequency (%)
210
30.2%
. 96
13.8%
5 49
 
7.0%
) 48
 
6.9%
- 48
 
6.9%
4 48
 
6.9%
( 48
 
6.9%
1 35
 
5.0%
, 27
 
3.9%
: 27
 
3.9%
Other values (7) 60
 
8.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1929
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
210
 
10.9%
a 136
 
7.1%
t 111
 
5.8%
e 110
 
5.7%
s 108
 
5.6%
. 96
 
5.0%
n 84
 
4.4%
d 83
 
4.3%
g 81
 
4.2%
r 81
 
4.2%
Other values (28) 829
43.0%

requirement2_5
Text

MISSING 

Distinct14
Distinct (%)82.4%
Missing423
Missing (%)96.1%
Memory size15.3 KiB
2023-12-09T22:07:27.964053image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length73
Median length73
Mean length61.52941176
Min length8

Characters and Unicode

Total characters1046
Distinct characters40
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique11 ?
Unique (%)64.7%

Sample

1st rowStandardized Test Scores: English Language Arts (2.1-4.5), Math (1.9-4.5)
2nd rowStandardized Test Scores: English Language Arts (1.8-4.5), Math (1.6-4.5)
3rd rowAttendance
4th rowAudition
5th rowStandardized Test Scores: English Language Arts (1.7-4.5), Math (1.6-4.5)
ValueCountFrequency (%)
standardized 14
10.9%
test 14
10.9%
scores 14
10.9%
english 14
10.9%
language 14
10.9%
arts 14
10.9%
math 14
10.9%
1.9-4.5 7
5.4%
1.8-4.5 5
 
3.9%
1.7-4.5 4
 
3.1%
Other values (10) 15
11.6%
2023-12-09T22:07:28.304123image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
112
 
10.7%
a 74
 
7.1%
t 63
 
6.0%
e 60
 
5.7%
s 56
 
5.4%
. 52
 
5.0%
n 49
 
4.7%
d 46
 
4.4%
r 42
 
4.0%
g 42
 
4.0%
Other values (30) 450
43.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 570
54.5%
Space Separator 112
 
10.7%
Decimal Number 104
 
9.9%
Uppercase Letter 102
 
9.8%
Other Punctuation 80
 
7.6%
Dash Punctuation 26
 
2.5%
Open Punctuation 26
 
2.5%
Close Punctuation 26
 
2.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 74
13.0%
t 63
11.1%
e 60
10.5%
s 56
9.8%
n 49
8.6%
d 46
8.1%
r 42
7.4%
g 42
7.4%
i 31
 
5.4%
h 28
 
4.9%
Other values (6) 79
13.9%
Decimal Number
ValueCountFrequency (%)
5 27
26.0%
4 26
25.0%
1 21
20.2%
9 7
 
6.7%
8 5
 
4.8%
7 4
 
3.8%
0 4
 
3.8%
2 4
 
3.8%
6 3
 
2.9%
3 3
 
2.9%
Uppercase Letter
ValueCountFrequency (%)
S 28
27.5%
A 17
16.7%
L 14
13.7%
T 14
13.7%
M 14
13.7%
E 14
13.7%
P 1
 
1.0%
Other Punctuation
ValueCountFrequency (%)
. 52
65.0%
, 14
 
17.5%
: 14
 
17.5%
Space Separator
ValueCountFrequency (%)
112
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 26
100.0%
Open Punctuation
ValueCountFrequency (%)
( 26
100.0%
Close Punctuation
ValueCountFrequency (%)
) 26
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 672
64.2%
Common 374
35.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 74
11.0%
t 63
 
9.4%
e 60
 
8.9%
s 56
 
8.3%
n 49
 
7.3%
d 46
 
6.8%
r 42
 
6.2%
g 42
 
6.2%
i 31
 
4.6%
S 28
 
4.2%
Other values (13) 181
26.9%
Common
ValueCountFrequency (%)
112
29.9%
. 52
13.9%
5 27
 
7.2%
- 26
 
7.0%
4 26
 
7.0%
( 26
 
7.0%
) 26
 
7.0%
1 21
 
5.6%
, 14
 
3.7%
: 14
 
3.7%
Other values (7) 30
 
8.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1046
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
112
 
10.7%
a 74
 
7.1%
t 63
 
6.0%
e 60
 
5.7%
s 56
 
5.4%
. 52
 
5.0%
n 49
 
4.7%
d 46
 
4.4%
r 42
 
4.0%
g 42
 
4.0%
Other values (30) 450
43.0%

requirement2_6
Text

MISSING 

Distinct9
Distinct (%)100.0%
Missing431
Missing (%)98.0%
Memory size14.7 KiB
2023-12-09T22:07:28.507727image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length73
Median length73
Mean length65.77777778
Min length8

Characters and Unicode

Total characters592
Distinct characters36
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9 ?
Unique (%)100.0%

Sample

1st rowStandardized Test Scores: English Language Arts (2.8-4.5), Math (2.8-4.5)
2nd rowStandardized Test Scores: English Language Arts (1.8-4.5), Math (1.6-4.5)
3rd rowStandardized Test Scores: English Language Arts (1.8-4.5), Math (1.8-4.5)
4th rowStandardized Test Scores: English Language Arts (1.8-4.5), Math (1.9-4.5)
5th rowAudition
ValueCountFrequency (%)
standardized 8
11.0%
test 8
11.0%
scores 8
11.0%
english 8
11.0%
language 8
11.0%
arts 8
11.0%
math 8
11.0%
1.8-4.5 5
6.8%
1.9-4.5 4
5.5%
2.8-4.5 2
 
2.7%
Other values (6) 6
8.2%
2023-12-09T22:07:28.835960image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
64
 
10.8%
a 40
 
6.8%
t 33
 
5.6%
e 32
 
5.4%
. 32
 
5.4%
s 32
 
5.4%
n 25
 
4.2%
d 25
 
4.2%
g 24
 
4.1%
r 24
 
4.1%
Other values (26) 261
44.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 311
52.5%
Space Separator 64
 
10.8%
Decimal Number 64
 
10.8%
Uppercase Letter 57
 
9.6%
Other Punctuation 48
 
8.1%
Close Punctuation 16
 
2.7%
Dash Punctuation 16
 
2.7%
Open Punctuation 16
 
2.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 40
12.9%
t 33
10.6%
e 32
10.3%
s 32
10.3%
n 25
8.0%
d 25
8.0%
g 24
7.7%
r 24
7.7%
i 18
5.8%
h 16
 
5.1%
Other values (5) 42
13.5%
Decimal Number
ValueCountFrequency (%)
5 16
25.0%
4 16
25.0%
1 12
18.8%
8 7
10.9%
9 5
 
7.8%
2 5
 
7.8%
3 2
 
3.1%
6 1
 
1.6%
Uppercase Letter
ValueCountFrequency (%)
S 16
28.1%
A 9
15.8%
T 8
14.0%
M 8
14.0%
L 8
14.0%
E 8
14.0%
Other Punctuation
ValueCountFrequency (%)
. 32
66.7%
, 8
 
16.7%
: 8
 
16.7%
Space Separator
ValueCountFrequency (%)
64
100.0%
Close Punctuation
ValueCountFrequency (%)
) 16
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 16
100.0%
Open Punctuation
ValueCountFrequency (%)
( 16
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 368
62.2%
Common 224
37.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 40
10.9%
t 33
 
9.0%
e 32
 
8.7%
s 32
 
8.7%
n 25
 
6.8%
d 25
 
6.8%
g 24
 
6.5%
r 24
 
6.5%
i 18
 
4.9%
S 16
 
4.3%
Other values (11) 99
26.9%
Common
ValueCountFrequency (%)
64
28.6%
. 32
14.3%
) 16
 
7.1%
5 16
 
7.1%
4 16
 
7.1%
- 16
 
7.1%
( 16
 
7.1%
1 12
 
5.4%
, 8
 
3.6%
: 8
 
3.6%
Other values (5) 20
 
8.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 592
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
64
 
10.8%
a 40
 
6.8%
t 33
 
5.6%
e 32
 
5.4%
. 32
 
5.4%
s 32
 
5.4%
n 25
 
4.2%
d 25
 
4.2%
g 24
 
4.1%
r 24
 
4.1%
Other values (26) 261
44.1%

requirement2_7
Text

MISSING 

Distinct6
Distinct (%)100.0%
Missing434
Missing (%)98.6%
Memory size14.4 KiB
2023-12-09T22:07:29.046342image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length73
Median length73
Mean length73
Min length73

Characters and Unicode

Total characters438
Distinct characters36
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)100.0%

Sample

1st rowStandardized Test Scores: English Language Arts (1.8-4.5), Math (1.6-4.5)
2nd rowStandardized Test Scores: English Language Arts (2.5-4.5), Math (2.4-4.5)
3rd rowStandardized Test Scores: English Language Arts (1.9-4.5), Math (1.9-4.5)
4th rowStandardized Test Scores: English Language Arts (2.1-4.5), Math (1.9-4.5)
5th rowStandardized Test Scores: English Language Arts (2.6-4.5), Math (2.9-4.5)
ValueCountFrequency (%)
standardized 6
11.1%
test 6
11.1%
scores 6
11.1%
english 6
11.1%
language 6
11.1%
arts 6
11.1%
math 6
11.1%
1.9-4.5 3
5.6%
2.5-4.5 2
 
3.7%
2.6-4.5 1
 
1.9%
Other values (6) 6
11.1%
2023-12-09T22:07:29.388803image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
48
 
11.0%
a 30
 
6.8%
e 24
 
5.5%
s 24
 
5.5%
. 24
 
5.5%
t 24
 
5.5%
g 18
 
4.1%
n 18
 
4.1%
d 18
 
4.1%
r 18
 
4.1%
Other values (26) 192
43.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 228
52.1%
Space Separator 48
 
11.0%
Decimal Number 48
 
11.0%
Uppercase Letter 42
 
9.6%
Other Punctuation 36
 
8.2%
Close Punctuation 12
 
2.7%
Dash Punctuation 12
 
2.7%
Open Punctuation 12
 
2.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 30
13.2%
e 24
10.5%
s 24
10.5%
t 24
10.5%
g 18
7.9%
n 18
7.9%
d 18
7.9%
r 18
7.9%
h 12
 
5.3%
i 12
 
5.3%
Other values (5) 30
13.2%
Decimal Number
ValueCountFrequency (%)
5 14
29.2%
4 13
27.1%
2 7
14.6%
1 6
12.5%
9 4
 
8.3%
6 2
 
4.2%
8 1
 
2.1%
7 1
 
2.1%
Uppercase Letter
ValueCountFrequency (%)
S 12
28.6%
E 6
14.3%
M 6
14.3%
T 6
14.3%
A 6
14.3%
L 6
14.3%
Other Punctuation
ValueCountFrequency (%)
. 24
66.7%
, 6
 
16.7%
: 6
 
16.7%
Space Separator
ValueCountFrequency (%)
48
100.0%
Close Punctuation
ValueCountFrequency (%)
) 12
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 12
100.0%
Open Punctuation
ValueCountFrequency (%)
( 12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 270
61.6%
Common 168
38.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 30
11.1%
e 24
 
8.9%
s 24
 
8.9%
t 24
 
8.9%
g 18
 
6.7%
n 18
 
6.7%
d 18
 
6.7%
r 18
 
6.7%
S 12
 
4.4%
h 12
 
4.4%
Other values (11) 72
26.7%
Common
ValueCountFrequency (%)
48
28.6%
. 24
14.3%
5 14
 
8.3%
4 13
 
7.7%
) 12
 
7.1%
- 12
 
7.1%
( 12
 
7.1%
2 7
 
4.2%
1 6
 
3.6%
, 6
 
3.6%
Other values (5) 14
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 438
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
48
 
11.0%
a 30
 
6.8%
e 24
 
5.5%
s 24
 
5.5%
. 24
 
5.5%
t 24
 
5.5%
g 18
 
4.1%
n 18
 
4.1%
d 18
 
4.1%
r 18
 
4.1%
Other values (26) 192
43.8%

requirement2_8
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing439
Missing (%)99.8%
Memory size14.0 KiB
2023-12-09T22:07:29.577366image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length73
Median length73
Mean length73
Min length73

Characters and Unicode

Total characters73
Distinct characters32
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowStandardized Test Scores: English Language Arts (1.9-4.5), Math (1.9-4.5)
ValueCountFrequency (%)
1.9-4.5 2
22.2%
standardized 1
11.1%
test 1
11.1%
scores 1
11.1%
english 1
11.1%
language 1
11.1%
arts 1
11.1%
math 1
11.1%
2023-12-09T22:07:29.874231image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8
 
11.0%
a 5
 
6.8%
e 4
 
5.5%
t 4
 
5.5%
. 4
 
5.5%
s 4
 
5.5%
g 3
 
4.1%
r 3
 
4.1%
d 3
 
4.1%
n 3
 
4.1%
Other values (22) 32
43.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 38
52.1%
Space Separator 8
 
11.0%
Decimal Number 8
 
11.0%
Uppercase Letter 7
 
9.6%
Other Punctuation 6
 
8.2%
Close Punctuation 2
 
2.7%
Dash Punctuation 2
 
2.7%
Open Punctuation 2
 
2.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 5
13.2%
e 4
10.5%
t 4
10.5%
s 4
10.5%
g 3
7.9%
r 3
7.9%
d 3
7.9%
n 3
7.9%
h 2
 
5.3%
i 2
 
5.3%
Other values (5) 5
13.2%
Uppercase Letter
ValueCountFrequency (%)
S 2
28.6%
L 1
14.3%
A 1
14.3%
E 1
14.3%
T 1
14.3%
M 1
14.3%
Decimal Number
ValueCountFrequency (%)
5 2
25.0%
4 2
25.0%
9 2
25.0%
1 2
25.0%
Other Punctuation
ValueCountFrequency (%)
. 4
66.7%
: 1
 
16.7%
, 1
 
16.7%
Space Separator
ValueCountFrequency (%)
8
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 45
61.6%
Common 28
38.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 5
11.1%
e 4
 
8.9%
t 4
 
8.9%
s 4
 
8.9%
g 3
 
6.7%
r 3
 
6.7%
d 3
 
6.7%
n 3
 
6.7%
h 2
 
4.4%
S 2
 
4.4%
Other values (11) 12
26.7%
Common
ValueCountFrequency (%)
8
28.6%
. 4
14.3%
5 2
 
7.1%
) 2
 
7.1%
4 2
 
7.1%
- 2
 
7.1%
9 2
 
7.1%
1 2
 
7.1%
( 2
 
7.1%
: 1
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 73
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
8
 
11.0%
a 5
 
6.8%
e 4
 
5.5%
t 4
 
5.5%
. 4
 
5.5%
s 4
 
5.5%
g 3
 
4.1%
r 3
 
4.1%
d 3
 
4.1%
n 3
 
4.1%
Other values (22) 32
43.8%

requirement2_9
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing440
Missing (%)100.0%
Memory size3.6 KiB

requirement2_10
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing440
Missing (%)100.0%
Memory size3.6 KiB

requirement3_1
Text

MISSING 

Distinct14
Distinct (%)15.1%
Missing347
Missing (%)78.9%
Memory size18.4 KiB
2023-12-09T22:07:30.137540image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length153
Median length26
Mean length24.31182796
Min length8

Characters and Unicode

Total characters2261
Distinct characters51
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8 ?
Unique (%)8.6%

Sample

1st rowAttendance and Punctuality
2nd rowWriting Exercise
3rd rowAttendance and Punctuality
4th rowAttendance and Punctuality
5th rowDemonstrated Special Talent
ValueCountFrequency (%)
attendance 70
26.8%
punctuality 56
21.5%
and 55
21.1%
interview 6
 
2.3%
audition 4
 
1.5%
writing 4
 
1.5%
exercise 4
 
1.5%
demonstrated 4
 
1.5%
scores 3
 
1.1%
math 3
 
1.1%
Other values (33) 52
19.9%
2023-12-09T22:07:30.543242image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
t 303
13.4%
n 288
12.7%
a 218
9.6%
e 198
8.8%
168
 
7.4%
d 146
 
6.5%
c 145
 
6.4%
u 120
 
5.3%
i 107
 
4.7%
A 78
 
3.4%
Other values (41) 490
21.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1821
80.5%
Uppercase Letter 199
 
8.8%
Space Separator 168
 
7.4%
Other Punctuation 26
 
1.1%
Decimal Number 24
 
1.1%
Open Punctuation 8
 
0.4%
Close Punctuation 8
 
0.4%
Dash Punctuation 7
 
0.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 303
16.6%
n 288
15.8%
a 218
12.0%
e 198
10.9%
d 146
8.0%
c 145
8.0%
u 120
 
6.6%
i 107
 
5.9%
l 71
 
3.9%
y 59
 
3.2%
Other values (11) 166
9.1%
Uppercase Letter
ValueCountFrequency (%)
A 78
39.2%
P 61
30.7%
S 16
 
8.0%
E 8
 
4.0%
I 8
 
4.0%
D 5
 
2.5%
W 4
 
2.0%
T 4
 
2.0%
M 4
 
2.0%
L 3
 
1.5%
Other values (5) 8
 
4.0%
Decimal Number
ValueCountFrequency (%)
4 7
29.2%
5 6
25.0%
1 5
20.8%
2 3
12.5%
7 1
 
4.2%
6 1
 
4.2%
9 1
 
4.2%
Other Punctuation
ValueCountFrequency (%)
. 12
46.2%
, 7
26.9%
: 6
23.1%
/ 1
 
3.8%
Space Separator
ValueCountFrequency (%)
168
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2020
89.3%
Common 241
 
10.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 303
15.0%
n 288
14.3%
a 218
10.8%
e 198
9.8%
d 146
7.2%
c 145
7.2%
u 120
 
5.9%
i 107
 
5.3%
A 78
 
3.9%
l 71
 
3.5%
Other values (26) 346
17.1%
Common
ValueCountFrequency (%)
168
69.7%
. 12
 
5.0%
( 8
 
3.3%
) 8
 
3.3%
4 7
 
2.9%
, 7
 
2.9%
- 7
 
2.9%
5 6
 
2.5%
: 6
 
2.5%
1 5
 
2.1%
Other values (5) 7
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2261
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t 303
13.4%
n 288
12.7%
a 218
9.6%
e 198
8.8%
168
 
7.4%
d 146
 
6.5%
c 145
 
6.4%
u 120
 
5.3%
i 107
 
4.7%
A 78
 
3.4%
Other values (41) 490
21.7%

requirement3_2
Text

MISSING 

Distinct6
Distinct (%)14.0%
Missing397
Missing (%)90.2%
Memory size16.0 KiB
2023-12-09T22:07:30.758880image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length73
Median length26
Mean length24.79069767
Min length8

Characters and Unicode

Total characters1066
Distinct characters39
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)4.7%

Sample

1st rowAttendance
2nd rowAttendance and Punctuality
3rd rowAttendance
4th rowAttendance and Punctuality
5th rowAttendance and Punctuality
ValueCountFrequency (%)
attendance 37
30.1%
punctuality 29
23.6%
and 29
23.6%
scores 2
 
1.6%
math 2
 
1.6%
3.3-4.5 2
 
1.6%
arts 2
 
1.6%
language 2
 
1.6%
english 2
 
1.6%
standardized 2
 
1.6%
Other values (7) 14
 
11.4%
2023-12-09T22:07:31.107703image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
t 152
14.3%
n 144
13.5%
a 107
10.0%
e 90
8.4%
80
 
7.5%
d 76
 
7.1%
c 70
 
6.6%
u 62
 
5.8%
A 41
 
3.8%
i 41
 
3.8%
Other values (29) 203
19.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 854
80.1%
Uppercase Letter 90
 
8.4%
Space Separator 80
 
7.5%
Decimal Number 16
 
1.5%
Other Punctuation 14
 
1.3%
Dash Punctuation 4
 
0.4%
Close Punctuation 4
 
0.4%
Open Punctuation 4
 
0.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 152
17.8%
n 144
16.9%
a 107
12.5%
e 90
10.5%
d 76
8.9%
c 70
8.2%
u 62
7.3%
i 41
 
4.8%
l 33
 
3.9%
y 29
 
3.4%
Other values (7) 50
 
5.9%
Uppercase Letter
ValueCountFrequency (%)
A 41
45.6%
P 29
32.2%
S 6
 
6.7%
L 2
 
2.2%
E 2
 
2.2%
T 2
 
2.2%
V 2
 
2.2%
I 2
 
2.2%
D 2
 
2.2%
M 2
 
2.2%
Decimal Number
ValueCountFrequency (%)
3 4
25.0%
4 4
25.0%
5 4
25.0%
1 2
12.5%
7 2
12.5%
Other Punctuation
ValueCountFrequency (%)
. 8
57.1%
: 4
28.6%
, 2
 
14.3%
Space Separator
ValueCountFrequency (%)
80
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 944
88.6%
Common 122
 
11.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 152
16.1%
n 144
15.3%
a 107
11.3%
e 90
9.5%
d 76
8.1%
c 70
7.4%
u 62
6.6%
A 41
 
4.3%
i 41
 
4.3%
l 33
 
3.5%
Other values (17) 128
13.6%
Common
ValueCountFrequency (%)
80
65.6%
. 8
 
6.6%
- 4
 
3.3%
3 4
 
3.3%
) 4
 
3.3%
4 4
 
3.3%
5 4
 
3.3%
( 4
 
3.3%
: 4
 
3.3%
, 2
 
1.6%
Other values (2) 4
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1066
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t 152
14.3%
n 144
13.5%
a 107
10.0%
e 90
8.4%
80
 
7.5%
d 76
 
7.1%
c 70
 
6.6%
u 62
 
5.8%
A 41
 
3.8%
i 41
 
3.8%
Other values (29) 203
19.0%

requirement3_3
Text

MISSING 

Distinct5
Distinct (%)14.7%
Missing406
Missing (%)92.3%
Memory size15.5 KiB
2023-12-09T22:07:31.314391image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length73
Median length26
Mean length22.82352941
Min length8

Characters and Unicode

Total characters776
Distinct characters38
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)5.9%

Sample

1st rowAttendance and Punctuality
2nd rowAttendance
3rd rowAttendance and Punctuality
4th rowAttendance and Punctuality
5th rowAudition
ValueCountFrequency (%)
attendance 30
33.7%
punctuality 22
24.7%
and 22
24.7%
audition 2
 
2.2%
scores 1
 
1.1%
math 1
 
1.1%
3.3-4.5 1
 
1.1%
arts 1
 
1.1%
language 1
 
1.1%
english 1
 
1.1%
Other values (7) 7
 
7.9%
2023-12-09T22:07:31.647878image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
t 115
14.8%
n 111
14.3%
a 80
10.3%
e 68
8.8%
d 58
7.5%
55
7.1%
c 54
7.0%
u 47
 
6.1%
A 33
 
4.3%
i 30
 
3.9%
Other values (28) 125
16.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 635
81.8%
Uppercase Letter 65
 
8.4%
Space Separator 55
 
7.1%
Decimal Number 8
 
1.0%
Other Punctuation 7
 
0.9%
Close Punctuation 2
 
0.3%
Dash Punctuation 2
 
0.3%
Open Punctuation 2
 
0.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 115
18.1%
n 111
17.5%
a 80
12.6%
e 68
10.7%
d 58
9.1%
c 54
8.5%
u 47
7.4%
i 30
 
4.7%
l 24
 
3.8%
y 22
 
3.5%
Other values (7) 26
 
4.1%
Uppercase Letter
ValueCountFrequency (%)
A 33
50.8%
P 22
33.8%
S 3
 
4.6%
L 1
 
1.5%
E 1
 
1.5%
T 1
 
1.5%
V 1
 
1.5%
I 1
 
1.5%
D 1
 
1.5%
M 1
 
1.5%
Decimal Number
ValueCountFrequency (%)
4 3
37.5%
5 2
25.0%
3 2
25.0%
0 1
 
12.5%
Other Punctuation
ValueCountFrequency (%)
. 4
57.1%
: 2
28.6%
, 1
 
14.3%
Space Separator
ValueCountFrequency (%)
55
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 700
90.2%
Common 76
 
9.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 115
16.4%
n 111
15.9%
a 80
11.4%
e 68
9.7%
d 58
8.3%
c 54
7.7%
u 47
6.7%
A 33
 
4.7%
i 30
 
4.3%
l 24
 
3.4%
Other values (17) 80
11.4%
Common
ValueCountFrequency (%)
55
72.4%
. 4
 
5.3%
4 3
 
3.9%
5 2
 
2.6%
) 2
 
2.6%
- 2
 
2.6%
3 2
 
2.6%
( 2
 
2.6%
: 2
 
2.6%
, 1
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 776
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t 115
14.8%
n 111
14.3%
a 80
10.3%
e 68
8.8%
d 58
7.5%
55
7.1%
c 54
7.0%
u 47
 
6.1%
A 33
 
4.3%
i 30
 
3.9%
Other values (28) 125
16.1%

requirement3_4
Text

MISSING 

Distinct3
Distinct (%)11.1%
Missing413
Missing (%)93.9%
Memory size15.1 KiB
2023-12-09T22:07:31.828314image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length26
Median length26
Mean length21.77777778
Min length8

Characters and Unicode

Total characters588
Distinct characters14
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)3.7%

Sample

1st rowAttendance and Punctuality
2nd rowAttendance
3rd rowAttendance and Punctuality
4th rowAttendance and Punctuality
5th rowAttendance and Punctuality
ValueCountFrequency (%)
attendance 26
38.8%
and 20
29.9%
punctuality 20
29.9%
audition 1
 
1.5%
2023-12-09T22:07:32.133385image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
t 93
15.8%
n 93
15.8%
a 66
11.2%
e 52
8.8%
d 47
8.0%
c 46
7.8%
u 41
7.0%
40
6.8%
A 27
 
4.6%
i 22
 
3.7%
Other values (4) 61
10.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 501
85.2%
Uppercase Letter 47
 
8.0%
Space Separator 40
 
6.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 93
18.6%
n 93
18.6%
a 66
13.2%
e 52
10.4%
d 47
9.4%
c 46
9.2%
u 41
8.2%
i 22
 
4.4%
l 20
 
4.0%
y 20
 
4.0%
Uppercase Letter
ValueCountFrequency (%)
A 27
57.4%
P 20
42.6%
Space Separator
ValueCountFrequency (%)
40
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 548
93.2%
Common 40
 
6.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 93
17.0%
n 93
17.0%
a 66
12.0%
e 52
9.5%
d 47
8.6%
c 46
8.4%
u 41
7.5%
A 27
 
4.9%
i 22
 
4.0%
P 20
 
3.6%
Other values (3) 41
7.5%
Common
ValueCountFrequency (%)
40
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 588
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t 93
15.8%
n 93
15.8%
a 66
11.2%
e 52
8.8%
d 47
8.0%
c 46
7.8%
u 41
7.0%
40
6.8%
A 27
 
4.6%
i 22
 
3.7%
Other values (4) 61
10.4%

requirement3_5
Text

MISSING 

Distinct4
Distinct (%)25.0%
Missing424
Missing (%)96.4%
Memory size14.6 KiB
2023-12-09T22:07:32.309047image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length26
Median length26
Mean length19.1875
Min length8

Characters and Unicode

Total characters307
Distinct characters19
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)12.5%

Sample

1st rowAttendance and Punctuality
2nd rowAttendance
3rd rowAudition
4th rowAttendance and Punctuality
5th rowArt Comparision
ValueCountFrequency (%)
attendance 14
40.0%
and 9
25.7%
punctuality 9
25.7%
art 1
 
2.9%
comparision 1
 
2.9%
audition 1
 
2.9%
2023-12-09T22:07:32.627316image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
t 48
15.6%
n 48
15.6%
a 33
10.7%
e 28
9.1%
d 24
7.8%
c 23
7.5%
u 19
 
6.2%
19
 
6.2%
A 16
 
5.2%
i 13
 
4.2%
Other values (9) 36
11.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 262
85.3%
Uppercase Letter 26
 
8.5%
Space Separator 19
 
6.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 48
18.3%
n 48
18.3%
a 33
12.6%
e 28
10.7%
d 24
9.2%
c 23
8.8%
u 19
 
7.3%
i 13
 
5.0%
l 9
 
3.4%
y 9
 
3.4%
Other values (5) 8
 
3.1%
Uppercase Letter
ValueCountFrequency (%)
A 16
61.5%
P 9
34.6%
C 1
 
3.8%
Space Separator
ValueCountFrequency (%)
19
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 288
93.8%
Common 19
 
6.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 48
16.7%
n 48
16.7%
a 33
11.5%
e 28
9.7%
d 24
8.3%
c 23
8.0%
u 19
 
6.6%
A 16
 
5.6%
i 13
 
4.5%
P 9
 
3.1%
Other values (8) 27
9.4%
Common
ValueCountFrequency (%)
19
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 307
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t 48
15.6%
n 48
15.6%
a 33
10.7%
e 28
9.1%
d 24
7.8%
c 23
7.5%
u 19
 
6.2%
19
 
6.2%
A 16
 
5.2%
i 13
 
4.2%
Other values (9) 36
11.7%

requirement3_6
Text

MISSING 

Distinct2
Distinct (%)25.0%
Missing432
Missing (%)98.2%
Memory size14.2 KiB
2023-12-09T22:07:32.793609image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length26
Median length26
Mean length22
Min length10

Characters and Unicode

Total characters176
Distinct characters13
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowAttendance and Punctuality
2nd rowAttendance
3rd rowAttendance and Punctuality
4th rowAttendance and Punctuality
5th rowAttendance and Punctuality
ValueCountFrequency (%)
attendance 8
40.0%
and 6
30.0%
punctuality 6
30.0%
2023-12-09T22:07:33.111341image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
t 28
15.9%
n 28
15.9%
a 20
11.4%
e 16
9.1%
d 14
8.0%
c 14
8.0%
12
6.8%
u 12
6.8%
A 8
 
4.5%
P 6
 
3.4%
Other values (3) 18
10.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 150
85.2%
Uppercase Letter 14
 
8.0%
Space Separator 12
 
6.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 28
18.7%
n 28
18.7%
a 20
13.3%
e 16
10.7%
d 14
9.3%
c 14
9.3%
u 12
8.0%
l 6
 
4.0%
i 6
 
4.0%
y 6
 
4.0%
Uppercase Letter
ValueCountFrequency (%)
A 8
57.1%
P 6
42.9%
Space Separator
ValueCountFrequency (%)
12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 164
93.2%
Common 12
 
6.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 28
17.1%
n 28
17.1%
a 20
12.2%
e 16
9.8%
d 14
8.5%
c 14
8.5%
u 12
7.3%
A 8
 
4.9%
P 6
 
3.7%
l 6
 
3.7%
Other values (2) 12
7.3%
Common
ValueCountFrequency (%)
12
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 176
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t 28
15.9%
n 28
15.9%
a 20
11.4%
e 16
9.1%
d 14
8.0%
c 14
8.0%
12
6.8%
u 12
6.8%
A 8
 
4.5%
P 6
 
3.4%
Other values (3) 18
10.2%

requirement3_7
Text

MISSING 

Distinct2
Distinct (%)33.3%
Missing434
Missing (%)98.6%
Memory size14.1 KiB
2023-12-09T22:07:33.291293image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length26
Median length26
Mean length20.66666667
Min length10

Characters and Unicode

Total characters124
Distinct characters13
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowAttendance and Punctuality
2nd rowAttendance and Punctuality
3rd rowAttendance
4th rowAttendance and Punctuality
5th rowAttendance
ValueCountFrequency (%)
attendance 6
42.9%
and 4
28.6%
punctuality 4
28.6%
2023-12-09T22:07:33.585726image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
t 20
16.1%
n 20
16.1%
a 14
11.3%
e 12
9.7%
d 10
8.1%
c 10
8.1%
8
 
6.5%
u 8
 
6.5%
A 6
 
4.8%
P 4
 
3.2%
Other values (3) 12
9.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 106
85.5%
Uppercase Letter 10
 
8.1%
Space Separator 8
 
6.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 20
18.9%
n 20
18.9%
a 14
13.2%
e 12
11.3%
d 10
9.4%
c 10
9.4%
u 8
 
7.5%
l 4
 
3.8%
i 4
 
3.8%
y 4
 
3.8%
Uppercase Letter
ValueCountFrequency (%)
A 6
60.0%
P 4
40.0%
Space Separator
ValueCountFrequency (%)
8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 116
93.5%
Common 8
 
6.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 20
17.2%
n 20
17.2%
a 14
12.1%
e 12
10.3%
d 10
8.6%
c 10
8.6%
u 8
 
6.9%
A 6
 
5.2%
P 4
 
3.4%
l 4
 
3.4%
Other values (2) 8
 
6.9%
Common
ValueCountFrequency (%)
8
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 124
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t 20
16.1%
n 20
16.1%
a 14
11.3%
e 12
9.7%
d 10
8.1%
c 10
8.1%
8
 
6.5%
u 8
 
6.5%
A 6
 
4.8%
P 4
 
3.2%
Other values (3) 12
9.7%

requirement3_8
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing439
Missing (%)99.8%
Memory size13.9 KiB
2023-12-09T22:07:33.754601image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length26
Median length26
Mean length26
Min length26

Characters and Unicode

Total characters26
Distinct characters13
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowAttendance and Punctuality
ValueCountFrequency (%)
attendance 1
33.3%
and 1
33.3%
punctuality 1
33.3%
2023-12-09T22:07:34.037167image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
t 4
15.4%
n 4
15.4%
a 3
11.5%
e 2
7.7%
d 2
7.7%
c 2
7.7%
2
7.7%
u 2
7.7%
A 1
 
3.8%
P 1
 
3.8%
Other values (3) 3
11.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 22
84.6%
Space Separator 2
 
7.7%
Uppercase Letter 2
 
7.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 4
18.2%
n 4
18.2%
a 3
13.6%
e 2
9.1%
d 2
9.1%
c 2
9.1%
u 2
9.1%
l 1
 
4.5%
i 1
 
4.5%
y 1
 
4.5%
Uppercase Letter
ValueCountFrequency (%)
A 1
50.0%
P 1
50.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 24
92.3%
Common 2
 
7.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 4
16.7%
n 4
16.7%
a 3
12.5%
e 2
8.3%
d 2
8.3%
c 2
8.3%
u 2
8.3%
A 1
 
4.2%
P 1
 
4.2%
l 1
 
4.2%
Other values (2) 2
8.3%
Common
ValueCountFrequency (%)
2
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 26
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t 4
15.4%
n 4
15.4%
a 3
11.5%
e 2
7.7%
d 2
7.7%
c 2
7.7%
2
7.7%
u 2
7.7%
A 1
 
3.8%
P 1
 
3.8%
Other values (3) 3
11.5%

requirement3_9
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing440
Missing (%)100.0%
Memory size3.6 KiB

requirement3_10
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing440
Missing (%)100.0%
Memory size3.6 KiB

requirement4_1
Text

MISSING 

Distinct23
Distinct (%)43.4%
Missing387
Missing (%)88.0%
Memory size16.5 KiB
2023-12-09T22:07:34.336594image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length227
Median length66
Mean length25.81132075
Min length8

Characters and Unicode

Total characters1368
Distinct characters52
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique16 ?
Unique (%)30.2%

Sample

1st rowWriting Exercise
2nd rowAudition
3rd rowDemonstrated Interest: School Visit or Written Contact
4th rowGroup Interview
5th rowAudition
ValueCountFrequency (%)
interview 15
 
8.4%
audition 10
 
5.6%
demonstrated 9
 
5.0%
writing 8
 
4.5%
interest 7
 
3.9%
school 7
 
3.9%
visit 7
 
3.9%
sample 4
 
2.2%
on-site 4
 
2.2%
exercise 4
 
2.2%
Other values (73) 104
58.1%
2023-12-09T22:07:34.782304image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 147
 
10.7%
t 135
 
9.9%
126
 
9.2%
i 116
 
8.5%
n 98
 
7.2%
o 86
 
6.3%
r 79
 
5.8%
s 79
 
5.8%
a 46
 
3.4%
d 37
 
2.7%
Other values (42) 419
30.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1068
78.1%
Uppercase Letter 131
 
9.6%
Space Separator 126
 
9.2%
Other Punctuation 28
 
2.0%
Open Punctuation 5
 
0.4%
Close Punctuation 5
 
0.4%
Dash Punctuation 4
 
0.3%
Decimal Number 1
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 147
13.8%
t 135
12.6%
i 116
10.9%
n 98
9.2%
o 86
8.1%
r 79
 
7.4%
s 79
 
7.4%
a 46
 
4.3%
d 37
 
3.5%
c 36
 
3.4%
Other values (13) 209
19.6%
Uppercase Letter
ValueCountFrequency (%)
A 22
16.8%
I 21
16.0%
S 15
11.5%
D 11
8.4%
W 11
8.4%
V 7
 
5.3%
T 7
 
5.3%
H 6
 
4.6%
E 5
 
3.8%
O 4
 
3.1%
Other values (10) 22
16.8%
Other Punctuation
ValueCountFrequency (%)
: 11
39.3%
, 8
28.6%
. 6
21.4%
/ 3
 
10.7%
Space Separator
ValueCountFrequency (%)
126
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%
Decimal Number
ValueCountFrequency (%)
9 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1199
87.6%
Common 169
 
12.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 147
12.3%
t 135
 
11.3%
i 116
 
9.7%
n 98
 
8.2%
o 86
 
7.2%
r 79
 
6.6%
s 79
 
6.6%
a 46
 
3.8%
d 37
 
3.1%
c 36
 
3.0%
Other values (33) 340
28.4%
Common
ValueCountFrequency (%)
126
74.6%
: 11
 
6.5%
, 8
 
4.7%
. 6
 
3.6%
( 5
 
3.0%
) 5
 
3.0%
- 4
 
2.4%
/ 3
 
1.8%
9 1
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1368
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 147
 
10.7%
t 135
 
9.9%
126
 
9.2%
i 116
 
8.5%
n 98
 
7.2%
o 86
 
6.3%
r 79
 
5.8%
s 79
 
5.8%
a 46
 
3.4%
d 37
 
2.7%
Other values (42) 419
30.6%

requirement4_2
Text

MISSING 

Distinct11
Distinct (%)42.3%
Missing414
Missing (%)94.1%
Memory size15.1 KiB
2023-12-09T22:07:35.050488image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length93
Median length68
Mean length24.07692308
Min length8

Characters and Unicode

Total characters626
Distinct characters50
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)23.1%

Sample

1st rowAudition
2nd rowAudition
3rd rowInterview
4th rowInterview
5th rowDemonstrated Special Talent: Athletics, Music, Fine Arts, or Dance
ValueCountFrequency (%)
audition 9
 
11.2%
interview 6
 
7.5%
demonstrated 4
 
5.0%
school 3
 
3.8%
dance 2
 
2.5%
to 2
 
2.5%
interest 2
 
2.5%
punctuality 2
 
2.5%
and 2
 
2.5%
attendance 2
 
2.5%
Other values (38) 46
57.5%
2023-12-09T22:07:35.462899image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 63
 
10.1%
t 62
 
9.9%
54
 
8.6%
i 51
 
8.1%
n 46
 
7.3%
o 39
 
6.2%
r 29
 
4.6%
s 28
 
4.5%
u 25
 
4.0%
d 22
 
3.5%
Other values (40) 207
33.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 481
76.8%
Uppercase Letter 73
 
11.7%
Space Separator 54
 
8.6%
Other Punctuation 12
 
1.9%
Close Punctuation 2
 
0.3%
Open Punctuation 2
 
0.3%
Dash Punctuation 2
 
0.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 63
13.1%
t 62
12.9%
i 51
10.6%
n 46
9.6%
o 39
8.1%
r 29
 
6.0%
s 28
 
5.8%
u 25
 
5.2%
d 22
 
4.6%
c 21
 
4.4%
Other values (14) 95
19.8%
Uppercase Letter
ValueCountFrequency (%)
A 18
24.7%
S 10
13.7%
I 8
11.0%
D 6
 
8.2%
P 5
 
6.8%
C 5
 
6.8%
T 3
 
4.1%
F 3
 
4.1%
R 2
 
2.7%
M 2
 
2.7%
Other values (9) 11
15.1%
Other Punctuation
ValueCountFrequency (%)
, 7
58.3%
: 4
33.3%
' 1
 
8.3%
Space Separator
ValueCountFrequency (%)
54
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 554
88.5%
Common 72
 
11.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 63
 
11.4%
t 62
 
11.2%
i 51
 
9.2%
n 46
 
8.3%
o 39
 
7.0%
r 29
 
5.2%
s 28
 
5.1%
u 25
 
4.5%
d 22
 
4.0%
c 21
 
3.8%
Other values (33) 168
30.3%
Common
ValueCountFrequency (%)
54
75.0%
, 7
 
9.7%
: 4
 
5.6%
) 2
 
2.8%
( 2
 
2.8%
- 2
 
2.8%
' 1
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 626
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 63
 
10.1%
t 62
 
9.9%
54
 
8.6%
i 51
 
8.1%
n 46
 
7.3%
o 39
 
6.2%
r 29
 
4.6%
s 28
 
4.5%
u 25
 
4.0%
d 22
 
3.5%
Other values (40) 207
33.1%

requirement4_3
Text

MISSING 

Distinct9
Distinct (%)45.0%
Missing420
Missing (%)95.5%
Memory size14.8 KiB
2023-12-09T22:07:35.701737image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length66
Median length45
Mean length22.05
Min length8

Characters and Unicode

Total characters441
Distinct characters42
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)30.0%

Sample

1st rowAudition
2nd rowAudition
3rd rowInterview
4th rowAudition
5th rowDemonstrated Interest: School Visit
ValueCountFrequency (%)
audition 8
 
14.8%
demonstrated 5
 
9.3%
interest 4
 
7.4%
school 4
 
7.4%
visit 4
 
7.4%
interview 2
 
3.7%
and 2
 
3.7%
on-site 2
 
3.7%
work 1
 
1.9%
portfolio 1
 
1.9%
Other values (21) 21
38.9%
2023-12-09T22:07:36.063112image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
t 51
 
11.6%
e 42
 
9.5%
i 38
 
8.6%
n 36
 
8.2%
34
 
7.7%
o 32
 
7.3%
s 24
 
5.4%
r 20
 
4.5%
d 18
 
4.1%
a 15
 
3.4%
Other values (32) 131
29.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 342
77.6%
Uppercase Letter 49
 
11.1%
Space Separator 34
 
7.7%
Other Punctuation 10
 
2.3%
Close Punctuation 2
 
0.5%
Dash Punctuation 2
 
0.5%
Open Punctuation 2
 
0.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 51
14.9%
e 42
12.3%
i 38
11.1%
n 36
10.5%
o 32
9.4%
s 24
7.0%
r 20
 
5.8%
d 18
 
5.3%
a 15
 
4.4%
c 15
 
4.4%
Other values (11) 51
14.9%
Uppercase Letter
ValueCountFrequency (%)
A 12
24.5%
S 7
14.3%
I 6
12.2%
D 6
12.2%
V 4
 
8.2%
M 3
 
6.1%
P 2
 
4.1%
O 2
 
4.1%
T 2
 
4.1%
F 1
 
2.0%
Other values (4) 4
 
8.2%
Other Punctuation
ValueCountFrequency (%)
: 5
50.0%
, 3
30.0%
/ 2
 
20.0%
Space Separator
ValueCountFrequency (%)
34
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 391
88.7%
Common 50
 
11.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 51
13.0%
e 42
10.7%
i 38
 
9.7%
n 36
 
9.2%
o 32
 
8.2%
s 24
 
6.1%
r 20
 
5.1%
d 18
 
4.6%
a 15
 
3.8%
c 15
 
3.8%
Other values (25) 100
25.6%
Common
ValueCountFrequency (%)
34
68.0%
: 5
 
10.0%
, 3
 
6.0%
) 2
 
4.0%
- 2
 
4.0%
( 2
 
4.0%
/ 2
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 441
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t 51
 
11.6%
e 42
 
9.5%
i 38
 
8.6%
n 36
 
8.2%
34
 
7.7%
o 32
 
7.3%
s 24
 
5.4%
r 20
 
4.5%
d 18
 
4.1%
a 15
 
3.4%
Other values (32) 131
29.7%

requirement4_4
Text

MISSING 

Distinct7
Distinct (%)50.0%
Missing426
Missing (%)96.8%
Memory size14.4 KiB
2023-12-09T22:07:36.268179image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length35
Median length31.5
Mean length15.92857143
Min length8

Characters and Unicode

Total characters223
Distinct characters40
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)35.7%

Sample

1st rowAudition
2nd rowAudition
3rd rowInterview
4th rowDemonstrated Interest: School Visit
5th rowInterview
ValueCountFrequency (%)
audition 7
25.0%
demonstrated 2
 
7.1%
interest 2
 
7.1%
school 2
 
7.1%
visit 2
 
7.1%
interview 2
 
7.1%
of 1
 
3.6%
response 1
 
3.6%
written 1
 
3.6%
work 1
 
3.6%
Other values (7) 7
25.0%
2023-12-09T22:07:36.596643image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
i 26
11.7%
t 25
 
11.2%
o 20
 
9.0%
e 19
 
8.5%
n 17
 
7.6%
14
 
6.3%
s 11
 
4.9%
r 10
 
4.5%
d 10
 
4.5%
u 8
 
3.6%
Other values (30) 63
28.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 176
78.9%
Uppercase Letter 27
 
12.1%
Space Separator 14
 
6.3%
Other Punctuation 3
 
1.3%
Dash Punctuation 1
 
0.4%
Open Punctuation 1
 
0.4%
Close Punctuation 1
 
0.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i 26
14.8%
t 25
14.2%
o 20
11.4%
e 19
10.8%
n 17
9.7%
s 11
6.2%
r 10
 
5.7%
d 10
 
5.7%
u 8
 
4.5%
l 5
 
2.8%
Other values (10) 25
14.2%
Uppercase Letter
ValueCountFrequency (%)
A 8
29.6%
S 4
14.8%
I 3
 
11.1%
D 2
 
7.4%
P 1
 
3.7%
O 1
 
3.7%
R 1
 
3.7%
W 1
 
3.7%
T 1
 
3.7%
L 1
 
3.7%
Other values (4) 4
14.8%
Other Punctuation
ValueCountFrequency (%)
: 2
66.7%
, 1
33.3%
Space Separator
ValueCountFrequency (%)
14
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 203
91.0%
Common 20
 
9.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
i 26
12.8%
t 25
12.3%
o 20
9.9%
e 19
 
9.4%
n 17
 
8.4%
s 11
 
5.4%
r 10
 
4.9%
d 10
 
4.9%
u 8
 
3.9%
A 8
 
3.9%
Other values (24) 49
24.1%
Common
ValueCountFrequency (%)
14
70.0%
: 2
 
10.0%
- 1
 
5.0%
( 1
 
5.0%
, 1
 
5.0%
) 1
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 223
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
i 26
11.7%
t 25
 
11.2%
o 20
 
9.0%
e 19
 
8.5%
n 17
 
7.6%
14
 
6.3%
s 11
 
4.9%
r 10
 
4.5%
d 10
 
4.5%
u 8
 
3.6%
Other values (30) 63
28.3%

requirement4_5
Text

MISSING 

Distinct4
Distinct (%)44.4%
Missing431
Missing (%)98.0%
Memory size14.2 KiB
2023-12-09T22:07:36.779633image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length54
Median length8
Mean length15.22222222
Min length8

Characters and Unicode

Total characters137
Distinct characters31
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)33.3%

Sample

1st rowAudition
2nd rowInterview
3rd rowAudition
4th rowAudition
5th rowAudition
ValueCountFrequency (%)
audition 6
35.3%
written 2
 
11.8%
demonstrated 1
 
5.9%
interest 1
 
5.9%
school 1
 
5.9%
visit 1
 
5.9%
or 1
 
5.9%
contact 1
 
5.9%
interview 1
 
5.9%
response 1
 
5.9%
2023-12-09T22:07:37.103244image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
t 19
13.9%
i 18
13.1%
n 14
10.2%
o 12
 
8.8%
e 11
 
8.0%
8
 
5.8%
d 7
 
5.1%
A 6
 
4.4%
u 6
 
4.4%
r 6
 
4.4%
Other values (21) 30
21.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 108
78.8%
Uppercase Letter 17
 
12.4%
Space Separator 8
 
5.8%
Dash Punctuation 1
 
0.7%
Open Punctuation 1
 
0.7%
Other Punctuation 1
 
0.7%
Close Punctuation 1
 
0.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 19
17.6%
i 18
16.7%
n 14
13.0%
o 12
11.1%
e 11
10.2%
d 7
 
6.5%
u 6
 
5.6%
r 6
 
5.6%
s 5
 
4.6%
a 2
 
1.9%
Other values (7) 8
7.4%
Uppercase Letter
ValueCountFrequency (%)
A 6
35.3%
I 2
 
11.8%
S 2
 
11.8%
W 2
 
11.8%
O 1
 
5.9%
R 1
 
5.9%
C 1
 
5.9%
V 1
 
5.9%
D 1
 
5.9%
Space Separator
ValueCountFrequency (%)
8
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Other Punctuation
ValueCountFrequency (%)
: 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 125
91.2%
Common 12
 
8.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 19
15.2%
i 18
14.4%
n 14
11.2%
o 12
9.6%
e 11
8.8%
d 7
 
5.6%
A 6
 
4.8%
u 6
 
4.8%
r 6
 
4.8%
s 5
 
4.0%
Other values (16) 21
16.8%
Common
ValueCountFrequency (%)
8
66.7%
- 1
 
8.3%
( 1
 
8.3%
: 1
 
8.3%
) 1
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 137
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t 19
13.9%
i 18
13.1%
n 14
10.2%
o 12
 
8.8%
e 11
 
8.0%
8
 
5.8%
d 7
 
5.1%
A 6
 
4.4%
u 6
 
4.4%
r 6
 
4.4%
Other values (21) 30
21.9%

requirement4_6
Text

MISSING 

Distinct2
Distinct (%)100.0%
Missing438
Missing (%)99.5%
Memory size14.0 KiB
2023-12-09T22:07:37.279627image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length26
Median length17
Mean length17
Min length8

Characters and Unicode

Total characters34
Distinct characters19
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st rowAudition
2nd rowWritten Response (On-Site)
ValueCountFrequency (%)
audition 1
25.0%
written 1
25.0%
response 1
25.0%
on-site 1
25.0%
2023-12-09T22:07:37.581587image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 4
11.8%
i 4
11.8%
t 4
11.8%
n 4
11.8%
s 2
 
5.9%
o 2
 
5.9%
2
 
5.9%
S 1
 
2.9%
- 1
 
2.9%
O 1
 
2.9%
Other values (9) 9
26.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 24
70.6%
Uppercase Letter 5
 
14.7%
Space Separator 2
 
5.9%
Dash Punctuation 1
 
2.9%
Open Punctuation 1
 
2.9%
Close Punctuation 1
 
2.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 4
16.7%
i 4
16.7%
t 4
16.7%
n 4
16.7%
s 2
8.3%
o 2
8.3%
p 1
 
4.2%
u 1
 
4.2%
r 1
 
4.2%
d 1
 
4.2%
Uppercase Letter
ValueCountFrequency (%)
S 1
20.0%
O 1
20.0%
A 1
20.0%
R 1
20.0%
W 1
20.0%
Space Separator
ValueCountFrequency (%)
2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 29
85.3%
Common 5
 
14.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 4
13.8%
i 4
13.8%
t 4
13.8%
n 4
13.8%
s 2
 
6.9%
o 2
 
6.9%
S 1
 
3.4%
O 1
 
3.4%
p 1
 
3.4%
A 1
 
3.4%
Other values (5) 5
17.2%
Common
ValueCountFrequency (%)
2
40.0%
- 1
20.0%
( 1
20.0%
) 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 34
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 4
11.8%
i 4
11.8%
t 4
11.8%
n 4
11.8%
s 2
 
5.9%
o 2
 
5.9%
2
 
5.9%
S 1
 
2.9%
- 1
 
2.9%
O 1
 
2.9%
Other values (9) 9
26.5%

requirement4_7
Text

MISSING 

Distinct2
Distinct (%)100.0%
Missing438
Missing (%)99.5%
Memory size14.0 KiB
2023-12-09T22:07:37.765110image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length35
Median length21.5
Mean length21.5
Min length8

Characters and Unicode

Total characters43
Distinct characters20
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st rowAudition
2nd rowDemonstrated interest: School Visit
ValueCountFrequency (%)
audition 1
20.0%
demonstrated 1
20.0%
interest 1
20.0%
school 1
20.0%
visit 1
20.0%
2023-12-09T22:07:38.073136image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
t 6
14.0%
i 5
11.6%
o 4
 
9.3%
e 4
 
9.3%
s 3
 
7.0%
n 3
 
7.0%
3
 
7.0%
d 2
 
4.7%
r 2
 
4.7%
: 1
 
2.3%
Other values (10) 10
23.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 35
81.4%
Uppercase Letter 4
 
9.3%
Space Separator 3
 
7.0%
Other Punctuation 1
 
2.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 6
17.1%
i 5
14.3%
o 4
11.4%
e 4
11.4%
s 3
8.6%
n 3
8.6%
d 2
 
5.7%
r 2
 
5.7%
l 1
 
2.9%
h 1
 
2.9%
Other values (4) 4
11.4%
Uppercase Letter
ValueCountFrequency (%)
S 1
25.0%
A 1
25.0%
D 1
25.0%
V 1
25.0%
Space Separator
ValueCountFrequency (%)
3
100.0%
Other Punctuation
ValueCountFrequency (%)
: 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 39
90.7%
Common 4
 
9.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 6
15.4%
i 5
12.8%
o 4
10.3%
e 4
10.3%
s 3
 
7.7%
n 3
 
7.7%
d 2
 
5.1%
r 2
 
5.1%
l 1
 
2.6%
h 1
 
2.6%
Other values (8) 8
20.5%
Common
ValueCountFrequency (%)
3
75.0%
: 1
 
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 43
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t 6
14.0%
i 5
11.6%
o 4
 
9.3%
e 4
 
9.3%
s 3
 
7.0%
n 3
 
7.0%
3
 
7.0%
d 2
 
4.7%
r 2
 
4.7%
: 1
 
2.3%
Other values (10) 10
23.3%

requirement4_8
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing440
Missing (%)100.0%
Memory size3.6 KiB

requirement4_9
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing440
Missing (%)100.0%
Memory size3.6 KiB

requirement4_10
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing440
Missing (%)100.0%
Memory size3.6 KiB

requirement5_1
Text

MISSING 

Distinct14
Distinct (%)66.7%
Missing419
Missing (%)95.2%
Memory size15.2 KiB
2023-12-09T22:07:38.344504image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length229
Median length35
Mean length28.61904762
Min length8

Characters and Unicode

Total characters601
Distinct characters48
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique11 ?
Unique (%)52.4%

Sample

1st rowGroup Interview (On-Site)
2nd rowPreference to students residing in the Lower East Side; interested students from all neighborhoods are encouraged to apply. Please contact the school for more information regarding this aspect of the schoolÂ’s selection criteria.
3rd rowWriting Exercise
4th rowWriting Sample
5th rowWriting Exercise
ValueCountFrequency (%)
writing 8
 
9.9%
exercise 7
 
8.6%
interview 4
 
4.9%
the 3
 
3.7%
on-site 3
 
3.7%
math 2
 
2.5%
students 2
 
2.5%
to 2
 
2.5%
house 2
 
2.5%
at 2
 
2.5%
Other values (41) 46
56.8%
2023-12-09T22:07:38.756594image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 73
12.1%
60
 
10.0%
i 51
 
8.5%
t 50
 
8.3%
r 43
 
7.2%
n 40
 
6.7%
s 37
 
6.2%
o 35
 
5.8%
a 22
 
3.7%
c 20
 
3.3%
Other values (38) 170
28.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 474
78.9%
Space Separator 60
 
10.0%
Uppercase Letter 50
 
8.3%
Other Punctuation 5
 
0.8%
Close Punctuation 4
 
0.7%
Open Punctuation 4
 
0.7%
Dash Punctuation 3
 
0.5%
Final Punctuation 1
 
0.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 73
15.4%
i 51
10.8%
t 50
10.5%
r 43
9.1%
n 40
8.4%
s 37
7.8%
o 35
 
7.4%
a 22
 
4.6%
c 20
 
4.2%
g 13
 
2.7%
Other values (13) 90
19.0%
Uppercase Letter
ValueCountFrequency (%)
W 8
16.0%
E 7
14.0%
S 6
12.0%
O 5
10.0%
I 5
10.0%
A 3
 
6.0%
H 3
 
6.0%
T 2
 
4.0%
M 2
 
4.0%
G 2
 
4.0%
Other values (6) 7
14.0%
Other Punctuation
ValueCountFrequency (%)
. 2
40.0%
/ 1
20.0%
; 1
20.0%
: 1
20.0%
Space Separator
ValueCountFrequency (%)
60
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Final Punctuation
ValueCountFrequency (%)
’ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 524
87.2%
Common 77
 
12.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 73
13.9%
i 51
 
9.7%
t 50
 
9.5%
r 43
 
8.2%
n 40
 
7.6%
s 37
 
7.1%
o 35
 
6.7%
a 22
 
4.2%
c 20
 
3.8%
g 13
 
2.5%
Other values (29) 140
26.7%
Common
ValueCountFrequency (%)
60
77.9%
) 4
 
5.2%
( 4
 
5.2%
- 3
 
3.9%
. 2
 
2.6%
/ 1
 
1.3%
’ 1
 
1.3%
; 1
 
1.3%
: 1
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 599
99.7%
Punctuation 1
 
0.2%
None 1
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 73
12.2%
60
 
10.0%
i 51
 
8.5%
t 50
 
8.3%
r 43
 
7.2%
n 40
 
6.7%
s 37
 
6.2%
o 35
 
5.8%
a 22
 
3.7%
c 20
 
3.3%
Other values (36) 168
28.0%
Punctuation
ValueCountFrequency (%)
’ 1
100.0%
None
ValueCountFrequency (%)
 1
100.0%

requirement5_2
Text

MISSING 

Distinct7
Distinct (%)58.3%
Missing428
Missing (%)97.3%
Memory size14.4 KiB
2023-12-09T22:07:38.971693image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length90
Median length21.5
Mean length20.08333333
Min length8

Characters and Unicode

Total characters241
Distinct characters31
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)33.3%

Sample

1st rowWriting Sample
2nd rowWriting Exercise
3rd rowPreference to Students in Closer Proximity to School; All Students are Encouraged to Apply
4th rowInterview
5th rowWriting Exercise
ValueCountFrequency (%)
writing 5
14.7%
exercise 4
 
11.8%
to 3
 
8.8%
interview 3
 
8.8%
students 2
 
5.9%
school 2
 
5.9%
sample 2
 
5.9%
preference 1
 
2.9%
in 1
 
2.9%
closer 1
 
2.9%
Other values (10) 10
29.4%
2023-12-09T22:07:39.299429image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 27
 
11.2%
i 24
 
10.0%
t 23
 
9.5%
22
 
9.1%
r 19
 
7.9%
n 16
 
6.6%
o 12
 
5.0%
c 9
 
3.7%
l 8
 
3.3%
W 7
 
2.9%
Other values (21) 74
30.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 190
78.8%
Uppercase Letter 28
 
11.6%
Space Separator 22
 
9.1%
Other Punctuation 1
 
0.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 27
14.2%
i 24
12.6%
t 23
12.1%
r 19
10.0%
n 16
8.4%
o 12
 
6.3%
c 9
 
4.7%
l 8
 
4.2%
s 7
 
3.7%
a 6
 
3.2%
Other values (11) 39
20.5%
Uppercase Letter
ValueCountFrequency (%)
W 7
25.0%
S 6
21.4%
E 4
14.3%
A 3
10.7%
I 3
10.7%
P 2
 
7.1%
C 2
 
7.1%
M 1
 
3.6%
Space Separator
ValueCountFrequency (%)
22
100.0%
Other Punctuation
ValueCountFrequency (%)
; 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 218
90.5%
Common 23
 
9.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 27
12.4%
i 24
 
11.0%
t 23
 
10.6%
r 19
 
8.7%
n 16
 
7.3%
o 12
 
5.5%
c 9
 
4.1%
l 8
 
3.7%
W 7
 
3.2%
s 7
 
3.2%
Other values (19) 66
30.3%
Common
ValueCountFrequency (%)
22
95.7%
; 1
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 241
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 27
 
11.2%
i 24
 
10.0%
t 23
 
9.5%
22
 
9.1%
r 19
 
7.9%
n 16
 
6.6%
o 12
 
5.0%
c 9
 
3.7%
l 8
 
3.3%
W 7
 
2.9%
Other values (21) 74
30.7%

requirement5_3
Text

MISSING 

Distinct8
Distinct (%)88.9%
Missing431
Missing (%)98.0%
Memory size14.3 KiB
2023-12-09T22:07:39.525567image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length68
Median length24
Mean length23.55555556
Min length8

Characters and Unicode

Total characters212
Distinct characters40
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7 ?
Unique (%)77.8%

Sample

1st rowProblem-Solving Exercise
2nd rowPreference to Students Who Have Passed All Four Core-Course Subjects
3rd rowWriting Sample
4th rowWriting Exercise
5th rowNYSESLAT Score, If Available
ValueCountFrequency (%)
writing 3
 
11.5%
exercise 3
 
11.5%
if 1
 
3.8%
score 1
 
3.8%
nyseslat 1
 
3.8%
sample 1
 
3.8%
interview 1
 
3.8%
audition 1
 
3.8%
subjects 1
 
3.8%
core-course 1
 
3.8%
Other values (12) 12
46.2%
2023-12-09T22:07:39.894471image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 26
 
12.3%
r 18
 
8.5%
17
 
8.0%
i 14
 
6.6%
o 13
 
6.1%
t 10
 
4.7%
s 10
 
4.7%
n 9
 
4.2%
c 9
 
4.2%
l 8
 
3.8%
Other values (30) 78
36.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 157
74.1%
Uppercase Letter 34
 
16.0%
Space Separator 17
 
8.0%
Dash Punctuation 2
 
0.9%
Other Punctuation 2
 
0.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 26
16.6%
r 18
11.5%
i 14
8.9%
o 13
 
8.3%
t 10
 
6.4%
s 10
 
6.4%
n 9
 
5.7%
c 9
 
5.7%
l 8
 
5.1%
u 6
 
3.8%
Other values (13) 34
21.7%
Uppercase Letter
ValueCountFrequency (%)
S 7
20.6%
A 5
14.7%
W 4
11.8%
E 4
11.8%
P 3
8.8%
C 2
 
5.9%
I 2
 
5.9%
H 2
 
5.9%
F 1
 
2.9%
N 1
 
2.9%
Other values (3) 3
8.8%
Other Punctuation
ValueCountFrequency (%)
/ 1
50.0%
, 1
50.0%
Space Separator
ValueCountFrequency (%)
17
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 191
90.1%
Common 21
 
9.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 26
 
13.6%
r 18
 
9.4%
i 14
 
7.3%
o 13
 
6.8%
t 10
 
5.2%
s 10
 
5.2%
n 9
 
4.7%
c 9
 
4.7%
l 8
 
4.2%
S 7
 
3.7%
Other values (26) 67
35.1%
Common
ValueCountFrequency (%)
17
81.0%
- 2
 
9.5%
/ 1
 
4.8%
, 1
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 212
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 26
 
12.3%
r 18
 
8.5%
17
 
8.0%
i 14
 
6.6%
o 13
 
6.1%
t 10
 
4.7%
s 10
 
4.7%
n 9
 
4.2%
c 9
 
4.2%
l 8
 
3.8%
Other values (30) 78
36.8%

requirement5_4
Text

MISSING 

Distinct6
Distinct (%)100.0%
Missing434
Missing (%)98.6%
Memory size14.2 KiB
2023-12-09T22:07:40.134847image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length54
Median length15
Mean length24.33333333
Min length8

Characters and Unicode

Total characters146
Distinct characters32
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)100.0%

Sample

1st rowWriting Sample
2nd rowInterview
3rd rowAudition
4th rowWriting exercise
5th rowHonors/Accelerated coursework in Math/Science
ValueCountFrequency (%)
writing 2
 
11.8%
demonstrated 1
 
5.9%
interest 1
 
5.9%
school 1
 
5.9%
visit 1
 
5.9%
or 1
 
5.9%
written 1
 
5.9%
contact 1
 
5.9%
interview 1
 
5.9%
exercise 1
 
5.9%
Other values (6) 6
35.3%
2023-12-09T22:07:40.504120image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 17
11.6%
t 15
 
10.3%
i 13
 
8.9%
r 12
 
8.2%
11
 
7.5%
n 11
 
7.5%
o 10
 
6.8%
c 8
 
5.5%
s 6
 
4.1%
a 5
 
3.4%
Other values (22) 38
26.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 117
80.1%
Uppercase Letter 15
 
10.3%
Space Separator 11
 
7.5%
Other Punctuation 3
 
2.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 17
14.5%
t 15
12.8%
i 13
11.1%
r 12
10.3%
n 11
9.4%
o 10
8.5%
c 8
6.8%
s 6
 
5.1%
a 5
 
4.3%
d 3
 
2.6%
Other values (10) 17
14.5%
Uppercase Letter
ValueCountFrequency (%)
S 3
20.0%
W 3
20.0%
A 2
13.3%
I 2
13.3%
H 1
 
6.7%
M 1
 
6.7%
D 1
 
6.7%
C 1
 
6.7%
V 1
 
6.7%
Other Punctuation
ValueCountFrequency (%)
/ 2
66.7%
: 1
33.3%
Space Separator
ValueCountFrequency (%)
11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 132
90.4%
Common 14
 
9.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 17
12.9%
t 15
11.4%
i 13
9.8%
r 12
 
9.1%
n 11
 
8.3%
o 10
 
7.6%
c 8
 
6.1%
s 6
 
4.5%
a 5
 
3.8%
d 3
 
2.3%
Other values (19) 32
24.2%
Common
ValueCountFrequency (%)
11
78.6%
/ 2
 
14.3%
: 1
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 146
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 17
11.6%
t 15
 
10.3%
i 13
 
8.9%
r 12
 
8.2%
11
 
7.5%
n 11
 
7.5%
o 10
 
6.8%
c 8
 
5.5%
s 6
 
4.1%
a 5
 
3.4%
Other values (22) 38
26.0%

requirement5_5
Text

MISSING 

Distinct3
Distinct (%)75.0%
Missing436
Missing (%)99.1%
Memory size14.0 KiB
2023-12-09T22:07:40.681267image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length16
Median length12.5
Mean length10.5
Min length8

Characters and Unicode

Total characters42
Distinct characters18
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)50.0%

Sample

1st rowInterview
2nd rowInterview
3rd rowAudition
4th rowWriting exercise
ValueCountFrequency (%)
interview 2
40.0%
writing 1
20.0%
exercise 1
20.0%
audition 1
20.0%
2023-12-09T22:07:40.989914image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 7
16.7%
i 7
16.7%
t 4
9.5%
r 4
9.5%
n 4
9.5%
I 2
 
4.8%
v 2
 
4.8%
w 2
 
4.8%
s 1
 
2.4%
d 1
 
2.4%
Other values (8) 8
19.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 37
88.1%
Uppercase Letter 4
 
9.5%
Space Separator 1
 
2.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 7
18.9%
i 7
18.9%
t 4
10.8%
r 4
10.8%
n 4
10.8%
v 2
 
5.4%
w 2
 
5.4%
s 1
 
2.7%
d 1
 
2.7%
u 1
 
2.7%
Other values (4) 4
10.8%
Uppercase Letter
ValueCountFrequency (%)
I 2
50.0%
A 1
25.0%
W 1
25.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 41
97.6%
Common 1
 
2.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 7
17.1%
i 7
17.1%
t 4
9.8%
r 4
9.8%
n 4
9.8%
I 2
 
4.9%
v 2
 
4.9%
w 2
 
4.9%
s 1
 
2.4%
d 1
 
2.4%
Other values (7) 7
17.1%
Common
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 42
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 7
16.7%
i 7
16.7%
t 4
9.5%
r 4
9.5%
n 4
9.5%
I 2
 
4.8%
v 2
 
4.8%
w 2
 
4.8%
s 1
 
2.4%
d 1
 
2.4%
Other values (8) 8
19.0%

requirement5_6
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing439
Missing (%)99.8%
Memory size13.9 KiB
2023-12-09T22:07:41.142109image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

Total characters8
Distinct characters7
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowAudition
ValueCountFrequency (%)
audition 1
100.0%
2023-12-09T22:07:41.407619image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
i 2
25.0%
A 1
12.5%
u 1
12.5%
d 1
12.5%
t 1
12.5%
o 1
12.5%
n 1
12.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 7
87.5%
Uppercase Letter 1
 
12.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i 2
28.6%
u 1
14.3%
d 1
14.3%
t 1
14.3%
o 1
14.3%
n 1
14.3%
Uppercase Letter
ValueCountFrequency (%)
A 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 8
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
i 2
25.0%
A 1
12.5%
u 1
12.5%
d 1
12.5%
t 1
12.5%
o 1
12.5%
n 1
12.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
i 2
25.0%
A 1
12.5%
u 1
12.5%
d 1
12.5%
t 1
12.5%
o 1
12.5%
n 1
12.5%

requirement5_7
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing439
Missing (%)99.8%
Memory size13.9 KiB
2023-12-09T22:07:41.591856image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length29
Median length29
Mean length29
Min length29

Characters and Unicode

Total characters29
Distinct characters18
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowHonors/Accelerated Coursework
ValueCountFrequency (%)
honors/accelerated 1
50.0%
coursework 1
50.0%
2023-12-09T22:07:41.910863image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
r 4
13.8%
e 4
13.8%
o 4
13.8%
s 2
 
6.9%
c 2
 
6.9%
H 1
 
3.4%
d 1
 
3.4%
w 1
 
3.4%
u 1
 
3.4%
C 1
 
3.4%
Other values (8) 8
27.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 24
82.8%
Uppercase Letter 3
 
10.3%
Space Separator 1
 
3.4%
Other Punctuation 1
 
3.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
r 4
16.7%
e 4
16.7%
o 4
16.7%
s 2
8.3%
c 2
8.3%
d 1
 
4.2%
w 1
 
4.2%
u 1
 
4.2%
l 1
 
4.2%
t 1
 
4.2%
Other values (3) 3
12.5%
Uppercase Letter
ValueCountFrequency (%)
H 1
33.3%
C 1
33.3%
A 1
33.3%
Space Separator
ValueCountFrequency (%)
1
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 27
93.1%
Common 2
 
6.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
r 4
14.8%
e 4
14.8%
o 4
14.8%
s 2
 
7.4%
c 2
 
7.4%
H 1
 
3.7%
d 1
 
3.7%
w 1
 
3.7%
u 1
 
3.7%
C 1
 
3.7%
Other values (6) 6
22.2%
Common
ValueCountFrequency (%)
1
50.0%
/ 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 29
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
r 4
13.8%
e 4
13.8%
o 4
13.8%
s 2
 
6.9%
c 2
 
6.9%
H 1
 
3.4%
d 1
 
3.4%
w 1
 
3.4%
u 1
 
3.4%
C 1
 
3.4%
Other values (8) 8
27.6%

requirement5_8
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing440
Missing (%)100.0%
Memory size3.6 KiB

requirement5_9
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing440
Missing (%)100.0%
Memory size3.6 KiB

requirement5_10
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing440
Missing (%)100.0%
Memory size3.6 KiB

requirement6_1
Text

MISSING 

Distinct3
Distinct (%)75.0%
Missing436
Missing (%)99.1%
Memory size14.0 KiB
2023-12-09T22:07:42.098837image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length25
Median length20.5
Mean length18
Min length15

Characters and Unicode

Total characters72
Distinct characters23
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)50.0%

Sample

1st rowPortfolio of student work
2nd rowWriting Exercise
3rd rowZoned to School
4th rowWriting Exercise
ValueCountFrequency (%)
writing 2
18.2%
exercise 2
18.2%
zoned 1
9.1%
to 1
9.1%
school 1
9.1%
portfolio 1
9.1%
of 1
9.1%
student 1
9.1%
work 1
9.1%
2023-12-09T22:07:42.409713image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o 9
12.5%
i 7
 
9.7%
7
 
9.7%
t 6
 
8.3%
e 6
 
8.3%
r 6
 
8.3%
n 4
 
5.6%
s 3
 
4.2%
c 3
 
4.2%
f 2
 
2.8%
Other values (13) 19
26.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 58
80.6%
Space Separator 7
 
9.7%
Uppercase Letter 7
 
9.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 9
15.5%
i 7
12.1%
t 6
10.3%
e 6
10.3%
r 6
10.3%
n 4
 
6.9%
s 3
 
5.2%
c 3
 
5.2%
f 2
 
3.4%
l 2
 
3.4%
Other values (7) 10
17.2%
Uppercase Letter
ValueCountFrequency (%)
W 2
28.6%
E 2
28.6%
Z 1
14.3%
S 1
14.3%
P 1
14.3%
Space Separator
ValueCountFrequency (%)
7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 65
90.3%
Common 7
 
9.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 9
13.8%
i 7
10.8%
t 6
 
9.2%
e 6
 
9.2%
r 6
 
9.2%
n 4
 
6.2%
s 3
 
4.6%
c 3
 
4.6%
f 2
 
3.1%
l 2
 
3.1%
Other values (12) 17
26.2%
Common
ValueCountFrequency (%)
7
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 72
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o 9
12.5%
i 7
 
9.7%
7
 
9.7%
t 6
 
8.3%
e 6
 
8.3%
r 6
 
8.3%
n 4
 
5.6%
s 3
 
4.2%
c 3
 
4.2%
f 2
 
2.8%
Other values (13) 19
26.4%

requirement6_2
Text

MISSING 

Distinct2
Distinct (%)100.0%
Missing438
Missing (%)99.5%
Memory size14.0 KiB
2023-12-09T22:07:42.602856image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length25
Median length20.5
Mean length20.5
Min length16

Characters and Unicode

Total characters41
Distinct characters20
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st rowWriting Exercise
2nd rowPortfolio of student work
ValueCountFrequency (%)
writing 1
16.7%
exercise 1
16.7%
portfolio 1
16.7%
of 1
16.7%
student 1
16.7%
work 1
16.7%
2023-12-09T22:07:42.924491image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o 5
12.2%
i 4
 
9.8%
t 4
 
9.8%
4
 
9.8%
r 4
 
9.8%
e 3
 
7.3%
f 2
 
4.9%
n 2
 
4.9%
s 2
 
4.9%
W 1
 
2.4%
Other values (10) 10
24.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 34
82.9%
Space Separator 4
 
9.8%
Uppercase Letter 3
 
7.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 5
14.7%
i 4
11.8%
t 4
11.8%
r 4
11.8%
e 3
8.8%
f 2
 
5.9%
n 2
 
5.9%
s 2
 
5.9%
w 1
 
2.9%
d 1
 
2.9%
Other values (6) 6
17.6%
Uppercase Letter
ValueCountFrequency (%)
W 1
33.3%
P 1
33.3%
E 1
33.3%
Space Separator
ValueCountFrequency (%)
4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 37
90.2%
Common 4
 
9.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 5
13.5%
i 4
10.8%
t 4
10.8%
r 4
10.8%
e 3
 
8.1%
f 2
 
5.4%
n 2
 
5.4%
s 2
 
5.4%
W 1
 
2.7%
w 1
 
2.7%
Other values (9) 9
24.3%
Common
ValueCountFrequency (%)
4
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 41
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o 5
12.2%
i 4
 
9.8%
t 4
 
9.8%
4
 
9.8%
r 4
 
9.8%
e 3
 
7.3%
f 2
 
4.9%
n 2
 
4.9%
s 2
 
4.9%
W 1
 
2.4%
Other values (10) 10
24.4%

requirement6_3
Text

MISSING 

Distinct2
Distinct (%)100.0%
Missing438
Missing (%)99.5%
Memory size14.0 KiB
2023-12-09T22:07:43.129310image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length90
Median length53
Mean length53
Min length16

Characters and Unicode

Total characters106
Distinct characters27
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st rowWriting Exercise
2nd rowPreference to Students in Closer Proximity to School; All Students are Encouraged to Apply
ValueCountFrequency (%)
to 3
18.8%
students 2
12.5%
preference 1
 
6.2%
in 1
 
6.2%
closer 1
 
6.2%
proximity 1
 
6.2%
school 1
 
6.2%
all 1
 
6.2%
are 1
 
6.2%
encouraged 1
 
6.2%
Other values (3) 3
18.8%
2023-12-09T22:07:43.472517image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
14
13.2%
e 11
 
10.4%
t 9
 
8.5%
o 8
 
7.5%
r 8
 
7.5%
i 6
 
5.7%
n 6
 
5.7%
l 5
 
4.7%
c 4
 
3.8%
s 4
 
3.8%
Other values (17) 31
29.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 80
75.5%
Space Separator 14
 
13.2%
Uppercase Letter 11
 
10.4%
Other Punctuation 1
 
0.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 11
13.8%
t 9
11.2%
o 8
10.0%
r 8
10.0%
i 6
 
7.5%
n 6
 
7.5%
l 5
 
6.2%
c 4
 
5.0%
s 4
 
5.0%
d 3
 
3.8%
Other values (9) 16
20.0%
Uppercase Letter
ValueCountFrequency (%)
S 3
27.3%
A 2
18.2%
E 2
18.2%
P 2
18.2%
C 1
 
9.1%
W 1
 
9.1%
Space Separator
ValueCountFrequency (%)
14
100.0%
Other Punctuation
ValueCountFrequency (%)
; 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 91
85.8%
Common 15
 
14.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 11
12.1%
t 9
 
9.9%
o 8
 
8.8%
r 8
 
8.8%
i 6
 
6.6%
n 6
 
6.6%
l 5
 
5.5%
c 4
 
4.4%
s 4
 
4.4%
d 3
 
3.3%
Other values (15) 27
29.7%
Common
ValueCountFrequency (%)
14
93.3%
; 1
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 106
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
14
13.2%
e 11
 
10.4%
t 9
 
8.5%
o 8
 
7.5%
r 8
 
7.5%
i 6
 
5.7%
n 6
 
5.7%
l 5
 
4.7%
c 4
 
3.8%
s 4
 
3.8%
Other values (17) 31
29.2%

requirement6_4
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing440
Missing (%)100.0%
Memory size3.6 KiB

requirement6_5
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing440
Missing (%)100.0%
Memory size3.6 KiB

requirement6_6
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing440
Missing (%)100.0%
Memory size3.6 KiB

requirement6_7
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing439
Missing (%)99.8%
Memory size13.9 KiB
2023-12-09T22:07:43.634203image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length15
Median length15
Mean length15
Min length15

Characters and Unicode

Total characters15
Distinct characters11
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowZoned to School
ValueCountFrequency (%)
zoned 1
33.3%
to 1
33.3%
school 1
33.3%
2023-12-09T22:07:43.925548image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o 4
26.7%
2
13.3%
Z 1
 
6.7%
n 1
 
6.7%
e 1
 
6.7%
d 1
 
6.7%
t 1
 
6.7%
S 1
 
6.7%
c 1
 
6.7%
h 1
 
6.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 11
73.3%
Space Separator 2
 
13.3%
Uppercase Letter 2
 
13.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 4
36.4%
n 1
 
9.1%
e 1
 
9.1%
d 1
 
9.1%
t 1
 
9.1%
c 1
 
9.1%
h 1
 
9.1%
l 1
 
9.1%
Uppercase Letter
ValueCountFrequency (%)
Z 1
50.0%
S 1
50.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 13
86.7%
Common 2
 
13.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 4
30.8%
Z 1
 
7.7%
n 1
 
7.7%
e 1
 
7.7%
d 1
 
7.7%
t 1
 
7.7%
S 1
 
7.7%
c 1
 
7.7%
h 1
 
7.7%
l 1
 
7.7%
Common
ValueCountFrequency (%)
2
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 15
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o 4
26.7%
2
13.3%
Z 1
 
6.7%
n 1
 
6.7%
e 1
 
6.7%
d 1
 
6.7%
t 1
 
6.7%
S 1
 
6.7%
c 1
 
6.7%
h 1
 
6.7%

requirement6_8
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing440
Missing (%)100.0%
Memory size3.6 KiB

requirement6_9
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing440
Missing (%)100.0%
Memory size3.6 KiB

requirement6_10
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing440
Missing (%)100.0%
Memory size3.6 KiB

requirement7_1
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing440
Missing (%)100.0%
Memory size3.6 KiB

requirement7_2
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing440
Missing (%)100.0%
Memory size3.6 KiB

requirement7_3
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing440
Missing (%)100.0%
Memory size3.6 KiB

requirement7_4
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing440
Missing (%)100.0%
Memory size3.6 KiB

requirement7_5
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing440
Missing (%)100.0%
Memory size3.6 KiB

requirement7_6
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing440
Missing (%)100.0%
Memory size3.6 KiB

requirement7_7
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing440
Missing (%)100.0%
Memory size3.6 KiB

requirement7_8
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing440
Missing (%)100.0%
Memory size3.6 KiB

requirement7_9
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing440
Missing (%)100.0%
Memory size3.6 KiB

requirement7_10
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing440
Missing (%)100.0%
Memory size3.6 KiB

requirement8_1
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing440
Missing (%)100.0%
Memory size3.6 KiB

requirement8_2
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing440
Missing (%)100.0%
Memory size3.6 KiB

requirement8_3
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing440
Missing (%)100.0%
Memory size3.6 KiB

requirement8_4
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing440
Missing (%)100.0%
Memory size3.6 KiB

requirement8_5
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing440
Missing (%)100.0%
Memory size3.6 KiB

requirement8_6
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing440
Missing (%)100.0%
Memory size3.6 KiB

requirement8_7
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing440
Missing (%)100.0%
Memory size3.6 KiB

requirement8_8
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing440
Missing (%)100.0%
Memory size3.6 KiB

requirement8_9
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing440
Missing (%)100.0%
Memory size3.6 KiB

requirement8_10
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing440
Missing (%)100.0%
Memory size3.6 KiB

requirement9_1
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing440
Missing (%)100.0%
Memory size3.6 KiB

requirement9_2
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing440
Missing (%)100.0%
Memory size3.6 KiB

requirement9_3
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing440
Missing (%)100.0%
Memory size3.6 KiB

requirement9_4
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing440
Missing (%)100.0%
Memory size3.6 KiB

requirement9_5
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing440
Missing (%)100.0%
Memory size3.6 KiB

requirement9_6
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing440
Missing (%)100.0%
Memory size3.6 KiB

requirement9_7
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing440
Missing (%)100.0%
Memory size3.6 KiB

requirement9_8
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing440
Missing (%)100.0%
Memory size3.6 KiB

requirement9_9
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing440
Missing (%)100.0%
Memory size3.6 KiB

requirement9_10
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing440
Missing (%)100.0%
Memory size3.6 KiB

requirement10_1
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing440
Missing (%)100.0%
Memory size3.6 KiB

requirement10_2
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing440
Missing (%)100.0%
Memory size3.6 KiB

requirement10_3
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing440
Missing (%)100.0%
Memory size3.6 KiB

requirement10_4
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing440
Missing (%)100.0%
Memory size3.6 KiB

requirement10_5
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing440
Missing (%)100.0%
Memory size3.6 KiB

requirement10_6
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing440
Missing (%)100.0%
Memory size3.6 KiB

requirement10_7
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing440
Missing (%)100.0%
Memory size3.6 KiB

requirement10_8
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing440
Missing (%)100.0%
Memory size3.6 KiB

requirement10_9
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing440
Missing (%)100.0%
Memory size3.6 KiB

requirement10_10
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing440
Missing (%)100.0%
Memory size3.6 KiB

requirement11_1
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing440
Missing (%)100.0%
Memory size3.6 KiB

requirement11_2
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing440
Missing (%)100.0%
Memory size3.6 KiB

requirement11_3
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing440
Missing (%)100.0%
Memory size3.6 KiB

requirement11_4
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing440
Missing (%)100.0%
Memory size3.6 KiB

requirement11_5
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing440
Missing (%)100.0%
Memory size3.6 KiB

requirement11_6
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing440
Missing (%)100.0%
Memory size3.6 KiB

requirement11_7
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing440
Missing (%)100.0%
Memory size3.6 KiB

requirement11_8
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing440
Missing (%)100.0%
Memory size3.6 KiB

requirement11_9
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing440
Missing (%)100.0%
Memory size3.6 KiB

requirement11_10
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing440
Missing (%)100.0%
Memory size3.6 KiB

requirement12_1
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing440
Missing (%)100.0%
Memory size3.6 KiB

requirement12_2
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing440
Missing (%)100.0%
Memory size3.6 KiB

requirement12_3
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing440
Missing (%)100.0%
Memory size3.6 KiB

requirement12_4
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing440
Missing (%)100.0%
Memory size3.6 KiB

requirement12_5
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing440
Missing (%)100.0%
Memory size3.6 KiB

requirement12_6
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing440
Missing (%)100.0%
Memory size3.6 KiB

requirement12_7
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing440
Missing (%)100.0%
Memory size3.6 KiB

requirement12_8
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing440
Missing (%)100.0%
Memory size3.6 KiB

requirement12_9
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing440
Missing (%)100.0%
Memory size3.6 KiB

requirement12_10
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing440
Missing (%)100.0%
Memory size3.6 KiB

offer_rate1
Text

MISSING 

Distinct95
Distinct (%)29.4%
Missing117
Missing (%)26.6%
Memory size51.6 KiB
2023-12-09T22:07:44.241081image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length78
Median length34
Mean length34.83591331
Min length30

Characters and Unicode

Total characters11252
Distinct characters32
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique22 ?
Unique (%)6.8%

Sample

1st row—57% of offers went to this group
2nd row—89% of offers went to this group
3rd row—87% of offers went to this group
4th row—14% of offers went to this group
5th row—35% of offers went to this group
ValueCountFrequency (%)
offers 317
13.9%
went 317
13.9%
to 317
13.9%
this 317
13.9%
group 317
13.9%
of 314
13.8%
â—100 33
 
1.4%
â—99 12
 
0.5%
â—96 9
 
0.4%
â—91 8
 
0.4%
Other values (101) 321
14.1%
2023-12-09T22:07:44.667536image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1959
17.4%
o 1304
11.6%
t 999
 
8.9%
f 960
 
8.5%
s 670
 
6.0%
e 664
 
5.9%
r 658
 
5.8%
n 374
 
3.3%
i 353
 
3.1%
 323
 
2.9%
Other values (22) 2988
26.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 7687
68.3%
Space Separator 1959
 
17.4%
Decimal Number 646
 
5.7%
Uppercase Letter 323
 
2.9%
Dash Punctuation 323
 
2.9%
Other Punctuation 314
 
2.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 1304
17.0%
t 999
13.0%
f 960
12.5%
s 670
8.7%
e 664
8.6%
r 658
8.6%
n 374
 
4.9%
i 353
 
4.6%
p 323
 
4.2%
u 323
 
4.2%
Other values (8) 1059
13.8%
Decimal Number
ValueCountFrequency (%)
9 96
14.9%
0 86
13.3%
1 81
12.5%
4 71
11.0%
8 64
9.9%
3 57
8.8%
6 56
8.7%
5 48
7.4%
2 44
6.8%
7 43
6.7%
Space Separator
ValueCountFrequency (%)
1959
100.0%
Uppercase Letter
ValueCountFrequency (%)
 323
100.0%
Dash Punctuation
ValueCountFrequency (%)
— 323
100.0%
Other Punctuation
ValueCountFrequency (%)
% 314
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 8010
71.2%
Common 3242
28.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 1304
16.3%
t 999
12.5%
f 960
12.0%
s 670
8.4%
e 664
8.3%
r 658
8.2%
n 374
 
4.7%
i 353
 
4.4%
 323
 
4.0%
p 323
 
4.0%
Other values (9) 1382
17.3%
Common
ValueCountFrequency (%)
1959
60.4%
— 323
 
10.0%
% 314
 
9.7%
9 96
 
3.0%
0 86
 
2.7%
1 81
 
2.5%
4 71
 
2.2%
8 64
 
2.0%
3 57
 
1.8%
6 56
 
1.7%
Other values (3) 135
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10606
94.3%
None 323
 
2.9%
Punctuation 323
 
2.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1959
18.5%
o 1304
12.3%
t 999
9.4%
f 960
9.1%
s 670
 
6.3%
e 664
 
6.3%
r 658
 
6.2%
n 374
 
3.5%
i 353
 
3.3%
p 323
 
3.0%
Other values (20) 2342
22.1%
None
ValueCountFrequency (%)
 323
100.0%
Punctuation
ValueCountFrequency (%)
— 323
100.0%

offer_rate2
Text

MISSING 

Distinct36
Distinct (%)62.1%
Missing382
Missing (%)86.8%
Memory size20.8 KiB
2023-12-09T22:07:44.936381image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length78
Median length34
Mean length36.4137931
Min length30

Characters and Unicode

Total characters2112
Distinct characters32
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique28 ?
Unique (%)48.3%

Sample

1st row—91% of offers went to this group
2nd row—31% of offers went to this group
3rd row—100% of offers went to this group
4th row—23% of offers went to this group
5th row—51% of offers went to this group
ValueCountFrequency (%)
offers 55
13.2%
went 55
13.2%
to 55
13.2%
this 55
13.2%
group 55
13.2%
of 54
12.9%
â—100 13
 
3.1%
information 3
 
0.7%
â—99 3
 
0.7%
students 3
 
0.7%
Other values (43) 67
16.0%
2023-12-09T22:07:45.416276image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
360
17.0%
o 238
11.3%
t 189
 
8.9%
f 170
 
8.0%
s 128
 
6.1%
e 125
 
5.9%
r 122
 
5.8%
n 83
 
3.9%
i 73
 
3.5%
 58
 
2.7%
Other values (22) 566
26.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1463
69.3%
Space Separator 360
 
17.0%
Decimal Number 119
 
5.6%
Uppercase Letter 58
 
2.7%
Dash Punctuation 58
 
2.7%
Other Punctuation 54
 
2.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 238
16.3%
t 189
12.9%
f 170
11.6%
s 128
8.7%
e 125
8.5%
r 122
8.3%
n 83
 
5.7%
i 73
 
5.0%
p 58
 
4.0%
u 58
 
4.0%
Other values (8) 219
15.0%
Decimal Number
ValueCountFrequency (%)
0 29
24.4%
1 29
24.4%
9 15
12.6%
8 11
 
9.2%
5 7
 
5.9%
3 7
 
5.9%
4 6
 
5.0%
6 6
 
5.0%
2 6
 
5.0%
7 3
 
2.5%
Space Separator
ValueCountFrequency (%)
360
100.0%
Uppercase Letter
ValueCountFrequency (%)
 58
100.0%
Dash Punctuation
ValueCountFrequency (%)
— 58
100.0%
Other Punctuation
ValueCountFrequency (%)
% 54
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1521
72.0%
Common 591
 
28.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 238
15.6%
t 189
12.4%
f 170
11.2%
s 128
8.4%
e 125
8.2%
r 122
8.0%
n 83
 
5.5%
i 73
 
4.8%
 58
 
3.8%
p 58
 
3.8%
Other values (9) 277
18.2%
Common
ValueCountFrequency (%)
360
60.9%
— 58
 
9.8%
% 54
 
9.1%
0 29
 
4.9%
1 29
 
4.9%
9 15
 
2.5%
8 11
 
1.9%
5 7
 
1.2%
3 7
 
1.2%
4 6
 
1.0%
Other values (3) 15
 
2.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1996
94.5%
None 58
 
2.7%
Punctuation 58
 
2.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
360
18.0%
o 238
11.9%
t 189
9.5%
f 170
 
8.5%
s 128
 
6.4%
e 125
 
6.3%
r 122
 
6.1%
n 83
 
4.2%
i 73
 
3.7%
p 58
 
2.9%
Other values (20) 450
22.5%
None
ValueCountFrequency (%)
 58
100.0%
Punctuation
ValueCountFrequency (%)
— 58
100.0%

offer_rate3
Text

MISSING 

Distinct14
Distinct (%)51.9%
Missing413
Missing (%)93.9%
Memory size17.1 KiB
2023-12-09T22:07:45.677113image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length78
Median length35
Mean length35.81481481
Min length30

Characters and Unicode

Total characters967
Distinct characters31
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique12 ?
Unique (%)44.4%

Sample

1st row—9% of offers went to this group
2nd row—97% of offers went to this group
3rd row—100% of offers went to this group
4th row—92% of offers went to this group
5th row—100% of offers went to this group
ValueCountFrequency (%)
offers 26
13.5%
went 26
13.5%
to 26
13.5%
this 26
13.5%
group 26
13.5%
of 25
13.0%
â—100 13
6.8%
â—9 2
 
1.0%
for 1
 
0.5%
at 1
 
0.5%
Other values (20) 20
10.4%
2023-12-09T22:07:46.059767image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
165
17.1%
o 110
11.4%
t 86
 
8.9%
f 79
 
8.2%
s 58
 
6.0%
e 57
 
5.9%
r 56
 
5.8%
n 36
 
3.7%
i 32
 
3.3%
p 27
 
2.8%
Other values (21) 261
27.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 664
68.7%
Space Separator 165
 
17.1%
Decimal Number 59
 
6.1%
Dash Punctuation 27
 
2.8%
Uppercase Letter 27
 
2.8%
Other Punctuation 25
 
2.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 110
16.6%
t 86
13.0%
f 79
11.9%
s 58
8.7%
e 57
8.6%
r 56
8.4%
n 36
 
5.4%
i 32
 
4.8%
p 27
 
4.1%
u 27
 
4.1%
Other values (8) 96
14.5%
Decimal Number
ValueCountFrequency (%)
0 27
45.8%
1 14
23.7%
9 6
 
10.2%
7 3
 
5.1%
5 3
 
5.1%
4 2
 
3.4%
2 2
 
3.4%
8 1
 
1.7%
3 1
 
1.7%
Space Separator
ValueCountFrequency (%)
165
100.0%
Dash Punctuation
ValueCountFrequency (%)
— 27
100.0%
Uppercase Letter
ValueCountFrequency (%)
 27
100.0%
Other Punctuation
ValueCountFrequency (%)
% 25
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 691
71.5%
Common 276
 
28.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 110
15.9%
t 86
12.4%
f 79
11.4%
s 58
8.4%
e 57
8.2%
r 56
8.1%
n 36
 
5.2%
i 32
 
4.6%
p 27
 
3.9%
u 27
 
3.9%
Other values (9) 123
17.8%
Common
ValueCountFrequency (%)
165
59.8%
— 27
 
9.8%
0 27
 
9.8%
% 25
 
9.1%
1 14
 
5.1%
9 6
 
2.2%
7 3
 
1.1%
5 3
 
1.1%
4 2
 
0.7%
2 2
 
0.7%
Other values (2) 2
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 913
94.4%
Punctuation 27
 
2.8%
None 27
 
2.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
165
18.1%
o 110
12.0%
t 86
9.4%
f 79
 
8.7%
s 58
 
6.4%
e 57
 
6.2%
r 56
 
6.1%
n 36
 
3.9%
i 32
 
3.5%
p 27
 
3.0%
Other values (19) 207
22.7%
Punctuation
ValueCountFrequency (%)
— 27
100.0%
None
ValueCountFrequency (%)
 27
100.0%

offer_rate4
Text

MISSING 

Distinct15
Distinct (%)71.4%
Missing419
Missing (%)95.2%
Memory size16.3 KiB
2023-12-09T22:07:46.279514image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length35
Median length34
Mean length34.04761905
Min length30

Characters and Unicode

Total characters715
Distinct characters27
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique13 ?
Unique (%)61.9%

Sample

1st row—6% of offers went to this group
2nd row—94% of offers went to this group
3rd row—96% of offers went to this group
4th row—97% of offers went to this group
5th row—100% of offers went to this group
ValueCountFrequency (%)
offers 21
14.4%
went 21
14.4%
to 21
14.4%
this 21
14.4%
group 21
14.4%
of 20
13.7%
â—100 6
 
4.1%
â—97 2
 
1.4%
â—6 1
 
0.7%
â—88 1
 
0.7%
Other values (11) 11
7.5%
2023-12-09T22:07:47.367223image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
125
17.5%
o 84
11.7%
t 63
 
8.8%
f 62
 
8.7%
e 42
 
5.9%
r 42
 
5.9%
s 42
 
5.9%
n 22
 
3.1%
h 21
 
2.9%
p 21
 
2.9%
Other values (17) 191
26.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 483
67.6%
Space Separator 125
 
17.5%
Decimal Number 45
 
6.3%
Uppercase Letter 21
 
2.9%
Dash Punctuation 21
 
2.9%
Other Punctuation 20
 
2.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 84
17.4%
t 63
13.0%
f 62
12.8%
e 42
8.7%
r 42
8.7%
s 42
8.7%
n 22
 
4.6%
h 21
 
4.3%
p 21
 
4.3%
u 21
 
4.3%
Other values (3) 63
13.0%
Decimal Number
ValueCountFrequency (%)
0 12
26.7%
9 8
17.8%
1 7
15.6%
7 3
 
6.7%
4 3
 
6.7%
6 3
 
6.7%
8 3
 
6.7%
5 2
 
4.4%
3 2
 
4.4%
2 2
 
4.4%
Space Separator
ValueCountFrequency (%)
125
100.0%
Uppercase Letter
ValueCountFrequency (%)
 21
100.0%
Dash Punctuation
ValueCountFrequency (%)
— 21
100.0%
Other Punctuation
ValueCountFrequency (%)
% 20
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 504
70.5%
Common 211
29.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 84
16.7%
t 63
12.5%
f 62
12.3%
e 42
8.3%
r 42
8.3%
s 42
8.3%
n 22
 
4.4%
h 21
 
4.2%
p 21
 
4.2%
u 21
 
4.2%
Other values (4) 84
16.7%
Common
ValueCountFrequency (%)
125
59.2%
— 21
 
10.0%
% 20
 
9.5%
0 12
 
5.7%
9 8
 
3.8%
1 7
 
3.3%
7 3
 
1.4%
4 3
 
1.4%
6 3
 
1.4%
8 3
 
1.4%
Other values (3) 6
 
2.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 673
94.1%
None 21
 
2.9%
Punctuation 21
 
2.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
125
18.6%
o 84
12.5%
t 63
9.4%
f 62
9.2%
e 42
 
6.2%
r 42
 
6.2%
s 42
 
6.2%
n 22
 
3.3%
h 21
 
3.1%
p 21
 
3.1%
Other values (15) 149
22.1%
None
ValueCountFrequency (%)
 21
100.0%
Punctuation
ValueCountFrequency (%)
— 21
100.0%

offer_rate5
Text

MISSING 

Distinct7
Distinct (%)53.8%
Missing427
Missing (%)97.0%
Memory size15.4 KiB
2023-12-09T22:07:47.570507image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length35
Median length34
Mean length33.92307692
Min length30

Characters and Unicode

Total characters441
Distinct characters23
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)30.8%

Sample

1st row—98% of offers went to this group
2nd row—100% of offers went to this group
3rd row—89% of offers went to this group
4th row—no offers went to this group
5th row—92% of offers went to this group
ValueCountFrequency (%)
offers 13
14.4%
went 13
14.4%
to 13
14.4%
this 13
14.4%
group 13
14.4%
of 12
13.3%
â—98 4
 
4.4%
â—100 3
 
3.3%
â—89 2
 
2.2%
â—44 1
 
1.1%
Other values (3) 3
 
3.3%
2023-12-09T22:07:47.895384image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
77
17.5%
o 52
11.8%
t 39
 
8.8%
f 38
 
8.6%
e 26
 
5.9%
r 26
 
5.9%
s 26
 
5.9%
n 14
 
3.2%
 13
 
2.9%
h 13
 
2.9%
Other values (13) 117
26.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 299
67.8%
Space Separator 77
 
17.5%
Decimal Number 27
 
6.1%
Uppercase Letter 13
 
2.9%
Dash Punctuation 13
 
2.9%
Other Punctuation 12
 
2.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 52
17.4%
t 39
13.0%
f 38
12.7%
e 26
8.7%
r 26
8.7%
s 26
8.7%
n 14
 
4.7%
h 13
 
4.3%
p 13
 
4.3%
u 13
 
4.3%
Other values (3) 39
13.0%
Decimal Number
ValueCountFrequency (%)
9 7
25.9%
8 6
22.2%
0 6
22.2%
1 4
14.8%
4 3
11.1%
2 1
 
3.7%
Space Separator
ValueCountFrequency (%)
77
100.0%
Uppercase Letter
ValueCountFrequency (%)
 13
100.0%
Dash Punctuation
ValueCountFrequency (%)
— 13
100.0%
Other Punctuation
ValueCountFrequency (%)
% 12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 312
70.7%
Common 129
29.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 52
16.7%
t 39
12.5%
f 38
12.2%
e 26
8.3%
r 26
8.3%
s 26
8.3%
n 14
 
4.5%
 13
 
4.2%
h 13
 
4.2%
p 13
 
4.2%
Other values (4) 52
16.7%
Common
ValueCountFrequency (%)
77
59.7%
— 13
 
10.1%
% 12
 
9.3%
9 7
 
5.4%
8 6
 
4.7%
0 6
 
4.7%
1 4
 
3.1%
4 3
 
2.3%
2 1
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 415
94.1%
None 13
 
2.9%
Punctuation 13
 
2.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
77
18.6%
o 52
12.5%
t 39
9.4%
f 38
9.2%
e 26
 
6.3%
r 26
 
6.3%
s 26
 
6.3%
n 14
 
3.4%
h 13
 
3.1%
p 13
 
3.1%
Other values (11) 91
21.9%
None
ValueCountFrequency (%)
 13
100.0%
Punctuation
ValueCountFrequency (%)
— 13
100.0%

offer_rate6
Text

MISSING 

Distinct5
Distinct (%)55.6%
Missing431
Missing (%)98.0%
Memory size14.9 KiB
2023-12-09T22:07:48.097311image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length35
Median length35
Mean length34.55555556
Min length34

Characters and Unicode

Total characters311
Distinct characters25
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)44.4%

Sample

1st row—100% of offers went to this group
2nd row—96% of offers went to this group
3rd row—56% of offers went to this group
4th row—42% of offers went to this group
5th row—100% of offers went to this group
ValueCountFrequency (%)
of 9
14.3%
offers 9
14.3%
went 9
14.3%
to 9
14.3%
this 9
14.3%
group 9
14.3%
â—100 5
7.9%
â—96 1
 
1.6%
â—42 1
 
1.6%
â—98 1
 
1.6%
2023-12-09T22:07:48.427782image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
54
17.4%
o 36
11.6%
f 27
 
8.7%
t 27
 
8.7%
e 18
 
5.8%
r 18
 
5.8%
s 18
 
5.8%
0 10
 
3.2%
 9
 
2.9%
h 9
 
2.9%
Other values (15) 85
27.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 207
66.6%
Space Separator 54
 
17.4%
Decimal Number 23
 
7.4%
Uppercase Letter 9
 
2.9%
Dash Punctuation 9
 
2.9%
Other Punctuation 9
 
2.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 36
17.4%
f 27
13.0%
t 27
13.0%
e 18
8.7%
r 18
8.7%
s 18
8.7%
h 9
 
4.3%
p 9
 
4.3%
u 9
 
4.3%
g 9
 
4.3%
Other values (3) 27
13.0%
Decimal Number
ValueCountFrequency (%)
0 10
43.5%
1 5
21.7%
9 2
 
8.7%
6 2
 
8.7%
4 1
 
4.3%
2 1
 
4.3%
8 1
 
4.3%
5 1
 
4.3%
Space Separator
ValueCountFrequency (%)
54
100.0%
Uppercase Letter
ValueCountFrequency (%)
 9
100.0%
Dash Punctuation
ValueCountFrequency (%)
— 9
100.0%
Other Punctuation
ValueCountFrequency (%)
% 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 216
69.5%
Common 95
30.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 36
16.7%
f 27
12.5%
t 27
12.5%
e 18
8.3%
r 18
8.3%
s 18
8.3%
 9
 
4.2%
h 9
 
4.2%
p 9
 
4.2%
u 9
 
4.2%
Other values (4) 36
16.7%
Common
ValueCountFrequency (%)
54
56.8%
0 10
 
10.5%
— 9
 
9.5%
% 9
 
9.5%
1 5
 
5.3%
9 2
 
2.1%
6 2
 
2.1%
4 1
 
1.1%
2 1
 
1.1%
8 1
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 293
94.2%
None 9
 
2.9%
Punctuation 9
 
2.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
54
18.4%
o 36
12.3%
f 27
9.2%
t 27
9.2%
e 18
 
6.1%
r 18
 
6.1%
s 18
 
6.1%
0 10
 
3.4%
h 9
 
3.1%
p 9
 
3.1%
Other values (13) 67
22.9%
None
ValueCountFrequency (%)
 9
100.0%
Punctuation
ValueCountFrequency (%)
— 9
100.0%

offer_rate7
Text

MISSING 

Distinct3
Distinct (%)60.0%
Missing435
Missing (%)98.9%
Memory size14.5 KiB
2023-12-09T22:07:48.629648image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length35
Median length35
Mean length34.6
Min length34

Characters and Unicode

Total characters173
Distinct characters23
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)40.0%

Sample

1st row—93% of offers went to this group
2nd row—48% of offers went to this group
3rd row—100% of offers went to this group
4th row—100% of offers went to this group
5th row—100% of offers went to this group
ValueCountFrequency (%)
of 5
14.3%
offers 5
14.3%
went 5
14.3%
to 5
14.3%
this 5
14.3%
group 5
14.3%
â—100 3
8.6%
â—93 1
 
2.9%
â—48 1
 
2.9%
2023-12-09T22:07:48.976025image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
30
17.3%
o 20
11.6%
f 15
 
8.7%
t 15
 
8.7%
e 10
 
5.8%
r 10
 
5.8%
s 10
 
5.8%
0 6
 
3.5%
 5
 
2.9%
h 5
 
2.9%
Other values (13) 47
27.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 115
66.5%
Space Separator 30
 
17.3%
Decimal Number 13
 
7.5%
Uppercase Letter 5
 
2.9%
Dash Punctuation 5
 
2.9%
Other Punctuation 5
 
2.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 20
17.4%
f 15
13.0%
t 15
13.0%
e 10
8.7%
r 10
8.7%
s 10
8.7%
h 5
 
4.3%
p 5
 
4.3%
u 5
 
4.3%
g 5
 
4.3%
Other values (3) 15
13.0%
Decimal Number
ValueCountFrequency (%)
0 6
46.2%
1 3
23.1%
9 1
 
7.7%
3 1
 
7.7%
4 1
 
7.7%
8 1
 
7.7%
Space Separator
ValueCountFrequency (%)
30
100.0%
Uppercase Letter
ValueCountFrequency (%)
 5
100.0%
Dash Punctuation
ValueCountFrequency (%)
— 5
100.0%
Other Punctuation
ValueCountFrequency (%)
% 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 120
69.4%
Common 53
30.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 20
16.7%
f 15
12.5%
t 15
12.5%
e 10
8.3%
r 10
8.3%
s 10
8.3%
 5
 
4.2%
h 5
 
4.2%
p 5
 
4.2%
u 5
 
4.2%
Other values (4) 20
16.7%
Common
ValueCountFrequency (%)
30
56.6%
0 6
 
11.3%
— 5
 
9.4%
% 5
 
9.4%
1 3
 
5.7%
9 1
 
1.9%
3 1
 
1.9%
4 1
 
1.9%
8 1
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 163
94.2%
None 5
 
2.9%
Punctuation 5
 
2.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
30
18.4%
o 20
12.3%
f 15
9.2%
t 15
9.2%
e 10
 
6.1%
r 10
 
6.1%
s 10
 
6.1%
0 6
 
3.7%
h 5
 
3.1%
p 5
 
3.1%
Other values (11) 37
22.7%
None
ValueCountFrequency (%)
 5
100.0%
Punctuation
ValueCountFrequency (%)
— 5
100.0%

offer_rate8
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)50.0%
Missing438
Missing (%)99.5%
Memory size14.1 KiB
2023-12-09T22:07:49.173730image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length35
Median length35
Mean length35
Min length35

Characters and Unicode

Total characters70
Distinct characters19
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row—100% of offers went to this group
2nd row—100% of offers went to this group
ValueCountFrequency (%)
â—100 2
14.3%
of 2
14.3%
offers 2
14.3%
went 2
14.3%
to 2
14.3%
this 2
14.3%
group 2
14.3%
2023-12-09T22:07:49.483446image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
12
17.1%
o 8
11.4%
t 6
 
8.6%
f 6
 
8.6%
r 4
 
5.7%
0 4
 
5.7%
e 4
 
5.7%
s 4
 
5.7%
u 2
 
2.9%
g 2
 
2.9%
Other values (9) 18
25.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 46
65.7%
Space Separator 12
 
17.1%
Decimal Number 6
 
8.6%
Uppercase Letter 2
 
2.9%
Dash Punctuation 2
 
2.9%
Other Punctuation 2
 
2.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 8
17.4%
t 6
13.0%
f 6
13.0%
r 4
8.7%
e 4
8.7%
s 4
8.7%
u 2
 
4.3%
g 2
 
4.3%
i 2
 
4.3%
h 2
 
4.3%
Other values (3) 6
13.0%
Decimal Number
ValueCountFrequency (%)
0 4
66.7%
1 2
33.3%
Space Separator
ValueCountFrequency (%)
12
100.0%
Uppercase Letter
ValueCountFrequency (%)
 2
100.0%
Dash Punctuation
ValueCountFrequency (%)
— 2
100.0%
Other Punctuation
ValueCountFrequency (%)
% 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 48
68.6%
Common 22
31.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 8
16.7%
t 6
12.5%
f 6
12.5%
r 4
8.3%
e 4
8.3%
s 4
8.3%
u 2
 
4.2%
g 2
 
4.2%
i 2
 
4.2%
h 2
 
4.2%
Other values (4) 8
16.7%
Common
ValueCountFrequency (%)
12
54.5%
0 4
 
18.2%
— 2
 
9.1%
% 2
 
9.1%
1 2
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 66
94.3%
None 2
 
2.9%
Punctuation 2
 
2.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
12
18.2%
o 8
12.1%
t 6
9.1%
f 6
9.1%
r 4
 
6.1%
0 4
 
6.1%
e 4
 
6.1%
s 4
 
6.1%
u 2
 
3.0%
g 2
 
3.0%
Other values (7) 14
21.2%
None
ValueCountFrequency (%)
 2
100.0%
Punctuation
ValueCountFrequency (%)
— 2
100.0%

offer_rate9
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing439
Missing (%)99.8%
Memory size14.0 KiB
2023-12-09T22:07:49.685224image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length34
Median length34
Mean length34
Min length34

Characters and Unicode

Total characters34
Distinct characters19
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row—96% of offers went to this group
ValueCountFrequency (%)
â—96 1
14.3%
of 1
14.3%
offers 1
14.3%
went 1
14.3%
to 1
14.3%
this 1
14.3%
group 1
14.3%
2023-12-09T22:07:49.994351image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6
17.6%
o 4
11.8%
f 3
 
8.8%
t 3
 
8.8%
r 2
 
5.9%
e 2
 
5.9%
s 2
 
5.9%
n 1
 
2.9%
u 1
 
2.9%
g 1
 
2.9%
Other values (9) 9
26.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 23
67.6%
Space Separator 6
 
17.6%
Decimal Number 2
 
5.9%
Uppercase Letter 1
 
2.9%
Dash Punctuation 1
 
2.9%
Other Punctuation 1
 
2.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 4
17.4%
f 3
13.0%
t 3
13.0%
r 2
8.7%
e 2
8.7%
s 2
8.7%
n 1
 
4.3%
u 1
 
4.3%
g 1
 
4.3%
i 1
 
4.3%
Other values (3) 3
13.0%
Decimal Number
ValueCountFrequency (%)
6 1
50.0%
9 1
50.0%
Space Separator
ValueCountFrequency (%)
6
100.0%
Uppercase Letter
ValueCountFrequency (%)
 1
100.0%
Dash Punctuation
ValueCountFrequency (%)
— 1
100.0%
Other Punctuation
ValueCountFrequency (%)
% 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 24
70.6%
Common 10
29.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 4
16.7%
f 3
12.5%
t 3
12.5%
r 2
8.3%
e 2
8.3%
s 2
8.3%
n 1
 
4.2%
u 1
 
4.2%
g 1
 
4.2%
i 1
 
4.2%
Other values (4) 4
16.7%
Common
ValueCountFrequency (%)
6
60.0%
— 1
 
10.0%
% 1
 
10.0%
6 1
 
10.0%
9 1
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 32
94.1%
None 1
 
2.9%
Punctuation 1
 
2.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6
18.8%
o 4
12.5%
f 3
9.4%
t 3
9.4%
r 2
 
6.2%
e 2
 
6.2%
s 2
 
6.2%
n 1
 
3.1%
u 1
 
3.1%
g 1
 
3.1%
Other values (7) 7
21.9%
None
ValueCountFrequency (%)
 1
100.0%
Punctuation
ValueCountFrequency (%)
— 1
100.0%

offer_rate10
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing440
Missing (%)100.0%
Memory size3.6 KiB

program1
Text

Distinct429
Distinct (%)97.5%
Missing0
Missing (%)0.0%
Memory size38.7 KiB
2023-12-09T22:07:50.370747image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length74
Median length52
Mean length31.71363636
Min length3

Characters and Unicode

Total characters13954
Distinct characters67
Distinct categories9 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique419 ?
Unique (%)95.2%

Sample

1st rowM.S. 260 Clinton School Writers & Artists
2nd rowLiberation Diploma Plus High School
3rd rowWomenÂ’s Academy of Excellence
4th rowPerforming and Visual Arts
5th rowEpic High School - South
ValueCountFrequency (%)
school 185
 
9.4%
high 115
 
5.8%
academy 104
 
5.3%
for 92
 
4.7%
and 81
 
4.1%
of 45
 
2.3%
the 45
 
2.3%
college 35
 
1.8%
technology 35
 
1.8%
arts 35
 
1.8%
Other values (458) 1194
60.7%
2023-12-09T22:07:50.942547image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1526
 
10.9%
e 1134
 
8.1%
o 1119
 
8.0%
a 889
 
6.4%
n 859
 
6.2%
i 795
 
5.7%
r 755
 
5.4%
l 627
 
4.5%
t 615
 
4.4%
c 614
 
4.4%
Other values (57) 5021
36.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 10500
75.2%
Uppercase Letter 1803
 
12.9%
Space Separator 1526
 
10.9%
Other Punctuation 86
 
0.6%
Dash Punctuation 16
 
0.1%
Open Punctuation 8
 
0.1%
Close Punctuation 8
 
0.1%
Final Punctuation 4
 
< 0.1%
Decimal Number 3
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 1134
10.8%
o 1119
10.7%
a 889
 
8.5%
n 859
 
8.2%
i 795
 
7.6%
r 755
 
7.2%
l 627
 
6.0%
t 615
 
5.9%
c 614
 
5.8%
h 520
 
5.0%
Other values (16) 2573
24.5%
Uppercase Letter
ValueCountFrequency (%)
S 308
17.1%
A 229
12.7%
H 176
9.8%
C 150
 
8.3%
T 104
 
5.8%
E 91
 
5.0%
P 91
 
5.0%
I 89
 
4.9%
M 88
 
4.9%
B 87
 
4.8%
Other values (16) 390
21.6%
Other Punctuation
ValueCountFrequency (%)
& 26
30.2%
, 21
24.4%
. 13
15.1%
/ 12
14.0%
: 9
 
10.5%
' 5
 
5.8%
Decimal Number
ValueCountFrequency (%)
2 1
33.3%
6 1
33.3%
0 1
33.3%
Dash Punctuation
ValueCountFrequency (%)
- 13
81.2%
– 3
 
18.8%
Space Separator
ValueCountFrequency (%)
1526
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8
100.0%
Final Punctuation
ValueCountFrequency (%)
’ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 12303
88.2%
Common 1651
 
11.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 1134
 
9.2%
o 1119
 
9.1%
a 889
 
7.2%
n 859
 
7.0%
i 795
 
6.5%
r 755
 
6.1%
l 627
 
5.1%
t 615
 
5.0%
c 614
 
5.0%
h 520
 
4.2%
Other values (42) 4376
35.6%
Common
ValueCountFrequency (%)
1526
92.4%
& 26
 
1.6%
, 21
 
1.3%
- 13
 
0.8%
. 13
 
0.8%
/ 12
 
0.7%
: 9
 
0.5%
( 8
 
0.5%
) 8
 
0.5%
' 5
 
0.3%
Other values (5) 10
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 13940
99.9%
None 7
 
0.1%
Punctuation 7
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1526
 
10.9%
e 1134
 
8.1%
o 1119
 
8.0%
a 889
 
6.4%
n 859
 
6.2%
i 795
 
5.7%
r 755
 
5.4%
l 627
 
4.5%
t 615
 
4.4%
c 614
 
4.4%
Other values (54) 5007
35.9%
None
ValueCountFrequency (%)
 7
100.0%
Punctuation
ValueCountFrequency (%)
’ 4
57.1%
– 3
42.9%

program2
Text

MISSING 

Distinct119
Distinct (%)93.0%
Missing312
Missing (%)70.9%
Memory size20.7 KiB
2023-12-09T22:07:51.208097image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length65
Median length43
Mean length28.125
Min length5

Characters and Unicode

Total characters3600
Distinct characters62
Distinct categories9 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique111 ?
Unique (%)86.7%

Sample

1st rowBronx School for Law, Government and Justice for Current Students
2nd rowCriminology and Forensics Institute (CFI)
3rd rowFranklin Center Science and Technology
4th rowFine Arts
5th rowCommunity Service Academy
ValueCountFrequency (%)
and 26
 
5.5%
academy 20
 
4.3%
institute 16
 
3.4%
technology 16
 
3.4%
for 13
 
2.8%
arts 12
 
2.6%
of 12
 
2.6%
college 9
 
1.9%
bilingual 9
 
1.9%
9
 
1.9%
Other values (174) 328
69.8%
2023-12-09T22:07:51.645230image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
342
 
9.5%
e 319
 
8.9%
n 273
 
7.6%
a 236
 
6.6%
i 234
 
6.5%
t 217
 
6.0%
r 215
 
6.0%
o 210
 
5.8%
s 164
 
4.6%
c 143
 
4.0%
Other values (52) 1247
34.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2762
76.7%
Uppercase Letter 447
 
12.4%
Space Separator 342
 
9.5%
Other Punctuation 26
 
0.7%
Dash Punctuation 11
 
0.3%
Close Punctuation 5
 
0.1%
Open Punctuation 5
 
0.1%
Decimal Number 1
 
< 0.1%
Other Number 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 319
11.5%
n 273
9.9%
a 236
 
8.5%
i 234
 
8.5%
t 217
 
7.9%
r 215
 
7.8%
o 210
 
7.6%
s 164
 
5.9%
c 143
 
5.2%
l 128
 
4.6%
Other values (15) 623
22.6%
Uppercase Letter
ValueCountFrequency (%)
S 55
12.3%
C 54
12.1%
A 51
11.4%
T 38
8.5%
M 36
8.1%
I 31
 
6.9%
P 30
 
6.7%
E 26
 
5.8%
B 20
 
4.5%
H 18
 
4.0%
Other values (14) 88
19.7%
Other Punctuation
ValueCountFrequency (%)
, 10
38.5%
& 9
34.6%
: 3
 
11.5%
/ 2
 
7.7%
' 2
 
7.7%
Dash Punctuation
ValueCountFrequency (%)
- 8
72.7%
– 2
 
18.2%
— 1
 
9.1%
Space Separator
ValueCountFrequency (%)
342
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Decimal Number
ValueCountFrequency (%)
8 1
100.0%
Other Number
ValueCountFrequency (%)
³ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 3209
89.1%
Common 391
 
10.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 319
 
9.9%
n 273
 
8.5%
a 236
 
7.4%
i 234
 
7.3%
t 217
 
6.8%
r 215
 
6.7%
o 210
 
6.5%
s 164
 
5.1%
c 143
 
4.5%
l 128
 
4.0%
Other values (39) 1070
33.3%
Common
ValueCountFrequency (%)
342
87.5%
, 10
 
2.6%
& 9
 
2.3%
- 8
 
2.0%
) 5
 
1.3%
( 5
 
1.3%
: 3
 
0.8%
/ 2
 
0.5%
' 2
 
0.5%
– 2
 
0.5%
Other values (3) 3
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3592
99.8%
None 5
 
0.1%
Punctuation 3
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
342
 
9.5%
e 319
 
8.9%
n 273
 
7.6%
a 236
 
6.6%
i 234
 
6.5%
t 217
 
6.0%
r 215
 
6.0%
o 210
 
5.8%
s 164
 
4.6%
c 143
 
4.0%
Other values (47) 1239
34.5%
None
ValueCountFrequency (%)
 3
60.0%
à 1
 
20.0%
³ 1
 
20.0%
Punctuation
ValueCountFrequency (%)
– 2
66.7%
— 1
33.3%

program3
Text

MISSING 

Distinct62
Distinct (%)88.6%
Missing370
Missing (%)84.1%
Memory size17.3 KiB
2023-12-09T22:07:51.922095image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length68
Median length38
Mean length25.11428571
Min length5

Characters and Unicode

Total characters1758
Distinct characters55
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique58 ?
Unique (%)82.9%

Sample

1st rowZoned
2nd rowInstrumental Music
3rd rowClassical Vocal Music
4th rowVisual Art
5th rowCulinary Arts
ValueCountFrequency (%)
institute 11
 
4.8%
and 10
 
4.4%
academy 9
 
3.9%
arts 9
 
3.9%
8
 
3.5%
science 7
 
3.1%
music 6
 
2.6%
of 6
 
2.6%
computer 5
 
2.2%
engineering 5
 
2.2%
Other values (111) 153
66.8%
2023-12-09T22:07:52.390364image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 160
 
9.1%
159
 
9.0%
n 137
 
7.8%
i 132
 
7.5%
t 117
 
6.7%
a 112
 
6.4%
r 106
 
6.0%
o 94
 
5.3%
s 89
 
5.1%
c 80
 
4.6%
Other values (45) 572
32.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1367
77.8%
Uppercase Letter 210
 
11.9%
Space Separator 159
 
9.0%
Other Punctuation 16
 
0.9%
Dash Punctuation 4
 
0.2%
Open Punctuation 1
 
0.1%
Close Punctuation 1
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 160
11.7%
n 137
10.0%
i 132
9.7%
t 117
8.6%
a 112
 
8.2%
r 106
 
7.8%
o 94
 
6.9%
s 89
 
6.5%
c 80
 
5.9%
u 57
 
4.2%
Other values (14) 283
20.7%
Uppercase Letter
ValueCountFrequency (%)
S 25
11.9%
A 23
11.0%
I 18
 
8.6%
C 18
 
8.6%
M 17
 
8.1%
P 16
 
7.6%
E 16
 
7.6%
T 12
 
5.7%
H 11
 
5.2%
L 8
 
3.8%
Other values (12) 46
21.9%
Other Punctuation
ValueCountFrequency (%)
& 8
50.0%
/ 3
 
18.8%
: 3
 
18.8%
' 1
 
6.2%
, 1
 
6.2%
Space Separator
ValueCountFrequency (%)
159
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1577
89.7%
Common 181
 
10.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 160
 
10.1%
n 137
 
8.7%
i 132
 
8.4%
t 117
 
7.4%
a 112
 
7.1%
r 106
 
6.7%
o 94
 
6.0%
s 89
 
5.6%
c 80
 
5.1%
u 57
 
3.6%
Other values (36) 493
31.3%
Common
ValueCountFrequency (%)
159
87.8%
& 8
 
4.4%
- 4
 
2.2%
/ 3
 
1.7%
: 3
 
1.7%
' 1
 
0.6%
, 1
 
0.6%
( 1
 
0.6%
) 1
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1758
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 160
 
9.1%
159
 
9.0%
n 137
 
7.8%
i 132
 
7.5%
t 117
 
6.7%
a 112
 
6.4%
r 106
 
6.0%
o 94
 
5.3%
s 89
 
5.1%
c 80
 
4.6%
Other values (45) 572
32.5%

program4
Text

MISSING 

Distinct42
Distinct (%)79.2%
Missing387
Missing (%)88.0%
Memory size16.3 KiB
2023-12-09T22:07:52.724832image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length67
Median length36
Mean length20.88679245
Min length4

Characters and Unicode

Total characters1107
Distinct characters51
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique38 ?
Unique (%)71.7%

Sample

1st rowVocal Music
2nd rowDance
3rd rowDrama
4th rowMedia Communication and Video Journalism
5th rowHumanities and the Arts
ValueCountFrequency (%)
institute 7
 
4.8%
and 7
 
4.8%
technology 6
 
4.1%
academy 6
 
4.1%
music 6
 
4.1%
drama 5
 
3.4%
5
 
3.4%
zoned 5
 
3.4%
science 4
 
2.7%
of 4
 
2.7%
Other values (66) 91
62.3%
2023-12-09T22:07:53.222185image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 102
 
9.2%
93
 
8.4%
n 86
 
7.8%
a 80
 
7.2%
i 71
 
6.4%
o 66
 
6.0%
t 63
 
5.7%
c 55
 
5.0%
r 52
 
4.7%
s 42
 
3.8%
Other values (41) 397
35.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 838
75.7%
Uppercase Letter 156
 
14.1%
Space Separator 93
 
8.4%
Other Punctuation 12
 
1.1%
Dash Punctuation 5
 
0.5%
Open Punctuation 1
 
0.1%
Final Punctuation 1
 
0.1%
Close Punctuation 1
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 102
12.2%
n 86
10.3%
a 80
9.5%
i 71
 
8.5%
o 66
 
7.9%
t 63
 
7.5%
c 55
 
6.6%
r 52
 
6.2%
s 42
 
5.0%
m 35
 
4.2%
Other values (11) 186
22.2%
Uppercase Letter
ValueCountFrequency (%)
M 25
16.0%
T 18
11.5%
S 16
10.3%
A 15
9.6%
D 12
7.7%
I 11
7.1%
C 10
 
6.4%
P 9
 
5.8%
E 9
 
5.8%
H 6
 
3.8%
Other values (10) 25
16.0%
Other Punctuation
ValueCountFrequency (%)
& 5
41.7%
. 4
33.3%
/ 2
 
16.7%
, 1
 
8.3%
Dash Punctuation
ValueCountFrequency (%)
- 4
80.0%
— 1
 
20.0%
Space Separator
ValueCountFrequency (%)
93
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Final Punctuation
ValueCountFrequency (%)
’ 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 994
89.8%
Common 113
 
10.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 102
 
10.3%
n 86
 
8.7%
a 80
 
8.0%
i 71
 
7.1%
o 66
 
6.6%
t 63
 
6.3%
c 55
 
5.5%
r 52
 
5.2%
s 42
 
4.2%
m 35
 
3.5%
Other values (31) 342
34.4%
Common
ValueCountFrequency (%)
93
82.3%
& 5
 
4.4%
- 4
 
3.5%
. 4
 
3.5%
/ 2
 
1.8%
( 1
 
0.9%
, 1
 
0.9%
’ 1
 
0.9%
— 1
 
0.9%
) 1
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1103
99.6%
None 2
 
0.2%
Punctuation 2
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 102
 
9.2%
93
 
8.4%
n 86
 
7.8%
a 80
 
7.3%
i 71
 
6.4%
o 66
 
6.0%
t 63
 
5.7%
c 55
 
5.0%
r 52
 
4.7%
s 42
 
3.8%
Other values (38) 393
35.6%
None
ValueCountFrequency (%)
 2
100.0%
Punctuation
ValueCountFrequency (%)
’ 1
50.0%
— 1
50.0%

program5
Text

MISSING 

Distinct33
Distinct (%)86.8%
Missing402
Missing (%)91.4%
Memory size15.8 KiB
2023-12-09T22:07:53.552164image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length55
Median length33
Mean length22.28947368
Min length5

Characters and Unicode

Total characters847
Distinct characters50
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique30 ?
Unique (%)78.9%

Sample

1st rowDance
2nd rowAir Force Junior ROTC
3rd rowEarly College Pharmacology
4th rowTheatre Arts
5th rowZoned
ValueCountFrequency (%)
academy 9
 
7.5%
and 8
 
6.7%
arts 7
 
5.8%
music 5
 
4.2%
of 5
 
4.2%
zoned 4
 
3.3%
visual 3
 
2.5%
instrumental 3
 
2.5%
the 3
 
2.5%
computer 3
 
2.5%
Other values (62) 70
58.3%
2023-12-09T22:07:54.032246image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
82
 
9.7%
e 70
 
8.3%
a 60
 
7.1%
n 54
 
6.4%
o 52
 
6.1%
r 50
 
5.9%
i 47
 
5.5%
t 45
 
5.3%
s 42
 
5.0%
c 38
 
4.5%
Other values (40) 307
36.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 646
76.3%
Uppercase Letter 113
 
13.3%
Space Separator 82
 
9.7%
Other Punctuation 3
 
0.4%
Dash Punctuation 2
 
0.2%
Final Punctuation 1
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 70
10.8%
a 60
 
9.3%
n 54
 
8.4%
o 52
 
8.0%
r 50
 
7.7%
i 47
 
7.3%
t 45
 
7.0%
s 42
 
6.5%
c 38
 
5.9%
m 33
 
5.1%
Other values (12) 155
24.0%
Uppercase Letter
ValueCountFrequency (%)
A 23
20.4%
T 10
 
8.8%
C 9
 
8.0%
D 7
 
6.2%
M 7
 
6.2%
I 6
 
5.3%
S 6
 
5.3%
P 5
 
4.4%
V 5
 
4.4%
R 4
 
3.5%
Other values (12) 31
27.4%
Other Punctuation
ValueCountFrequency (%)
& 2
66.7%
, 1
33.3%
Dash Punctuation
ValueCountFrequency (%)
– 1
50.0%
— 1
50.0%
Space Separator
ValueCountFrequency (%)
82
100.0%
Final Punctuation
ValueCountFrequency (%)
’ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 759
89.6%
Common 88
 
10.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 70
 
9.2%
a 60
 
7.9%
n 54
 
7.1%
o 52
 
6.9%
r 50
 
6.6%
i 47
 
6.2%
t 45
 
5.9%
s 42
 
5.5%
c 38
 
5.0%
m 33
 
4.3%
Other values (34) 268
35.3%
Common
ValueCountFrequency (%)
82
93.2%
& 2
 
2.3%
, 1
 
1.1%
– 1
 
1.1%
— 1
 
1.1%
’ 1
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 841
99.3%
None 3
 
0.4%
Punctuation 3
 
0.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
82
 
9.8%
e 70
 
8.3%
a 60
 
7.1%
n 54
 
6.4%
o 52
 
6.2%
r 50
 
5.9%
i 47
 
5.6%
t 45
 
5.4%
s 42
 
5.0%
c 38
 
4.5%
Other values (36) 301
35.8%
None
ValueCountFrequency (%)
 3
100.0%
Punctuation
ValueCountFrequency (%)
– 1
33.3%
— 1
33.3%
’ 1
33.3%

program6
Text

MISSING 

Distinct20
Distinct (%)83.3%
Missing416
Missing (%)94.5%
Memory size14.9 KiB
2023-12-09T22:07:54.313522image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length39
Median length33
Mean length19.08333333
Min length5

Characters and Unicode

Total characters458
Distinct characters44
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique19 ?
Unique (%)79.2%

Sample

1st rowDrama
2nd rowPre-Engineering and Applied Mathematics
3rd rowComputer Technology
4th rowAcademy of Public Service and Law
5th rowZoned
ValueCountFrequency (%)
academy 6
 
9.4%
zoned 5
 
7.8%
and 5
 
7.8%
of 4
 
6.2%
technology 4
 
6.2%
fine 3
 
4.7%
arts 3
 
4.7%
nursing 2
 
3.1%
computer 2
 
3.1%
s.t.e.m 1
 
1.6%
Other values (29) 29
45.3%
2023-12-09T22:07:54.723771image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 42
 
9.2%
40
 
8.7%
n 35
 
7.6%
a 31
 
6.8%
o 27
 
5.9%
i 26
 
5.7%
d 21
 
4.6%
c 21
 
4.6%
r 20
 
4.4%
t 19
 
4.1%
Other values (34) 176
38.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 348
76.0%
Uppercase Letter 62
 
13.5%
Space Separator 40
 
8.7%
Other Punctuation 7
 
1.5%
Dash Punctuation 1
 
0.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 42
12.1%
n 35
 
10.1%
a 31
 
8.9%
o 27
 
7.8%
i 26
 
7.5%
d 21
 
6.0%
c 21
 
6.0%
r 20
 
5.7%
t 19
 
5.5%
s 18
 
5.2%
Other values (11) 88
25.3%
Uppercase Letter
ValueCountFrequency (%)
A 13
21.0%
M 7
11.3%
T 7
11.3%
Z 5
 
8.1%
S 5
 
8.1%
E 4
 
6.5%
P 4
 
6.5%
F 3
 
4.8%
D 2
 
3.2%
C 2
 
3.2%
Other values (8) 10
16.1%
Other Punctuation
ValueCountFrequency (%)
. 4
57.1%
/ 2
28.6%
& 1
 
14.3%
Space Separator
ValueCountFrequency (%)
40
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 410
89.5%
Common 48
 
10.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 42
 
10.2%
n 35
 
8.5%
a 31
 
7.6%
o 27
 
6.6%
i 26
 
6.3%
d 21
 
5.1%
c 21
 
5.1%
r 20
 
4.9%
t 19
 
4.6%
s 18
 
4.4%
Other values (29) 150
36.6%
Common
ValueCountFrequency (%)
40
83.3%
. 4
 
8.3%
/ 2
 
4.2%
- 1
 
2.1%
& 1
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 458
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 42
 
9.2%
40
 
8.7%
n 35
 
7.6%
a 31
 
6.8%
o 27
 
5.9%
i 26
 
5.7%
d 21
 
4.6%
c 21
 
4.6%
r 20
 
4.4%
t 19
 
4.1%
Other values (34) 176
38.4%

program7
Text

MISSING 

Distinct12
Distinct (%)85.7%
Missing426
Missing (%)96.8%
Memory size14.4 KiB
2023-12-09T22:07:54.950439image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length33
Median length23.5
Mean length16.21428571
Min length5

Characters and Unicode

Total characters227
Distinct characters35
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique11 ?
Unique (%)78.6%

Sample

1st rowZoned
2nd rowBiz/Tech
3rd rowConstruction/Carpentry
4th rowArt History & Fine Arts
5th rowDual Language Spanish Program
ValueCountFrequency (%)
zoned 3
 
9.7%
arts 2
 
6.5%
2
 
6.5%
program 2
 
6.5%
technology 1
 
3.2%
fine 1
 
3.2%
history 1
 
3.2%
art 1
 
3.2%
honors 1
 
3.2%
academy 1
 
3.2%
Other values (16) 16
51.6%
2023-12-09T22:07:55.316753image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 22
 
9.7%
r 19
 
8.4%
17
 
7.5%
o 17
 
7.5%
n 16
 
7.0%
t 16
 
7.0%
a 15
 
6.6%
i 12
 
5.3%
s 8
 
3.5%
g 7
 
3.1%
Other values (25) 78
34.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 175
77.1%
Uppercase Letter 31
 
13.7%
Space Separator 17
 
7.5%
Other Punctuation 4
 
1.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 22
12.6%
r 19
10.9%
o 17
9.7%
n 16
9.1%
t 16
9.1%
a 15
8.6%
i 12
 
6.9%
s 8
 
4.6%
g 7
 
4.0%
c 7
 
4.0%
Other values (9) 36
20.6%
Uppercase Letter
ValueCountFrequency (%)
C 4
12.9%
A 4
12.9%
T 4
12.9%
Z 3
9.7%
P 3
9.7%
S 3
9.7%
I 2
6.5%
M 2
6.5%
H 2
6.5%
D 1
 
3.2%
Other values (3) 3
9.7%
Other Punctuation
ValueCountFrequency (%)
& 2
50.0%
/ 2
50.0%
Space Separator
ValueCountFrequency (%)
17
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 206
90.7%
Common 21
 
9.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 22
 
10.7%
r 19
 
9.2%
o 17
 
8.3%
n 16
 
7.8%
t 16
 
7.8%
a 15
 
7.3%
i 12
 
5.8%
s 8
 
3.9%
g 7
 
3.4%
c 7
 
3.4%
Other values (22) 67
32.5%
Common
ValueCountFrequency (%)
17
81.0%
& 2
 
9.5%
/ 2
 
9.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 227
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 22
 
9.7%
r 19
 
8.4%
17
 
7.5%
o 17
 
7.5%
n 16
 
7.0%
t 16
 
7.0%
a 15
 
6.6%
i 12
 
5.3%
s 8
 
3.5%
g 7
 
3.1%
Other values (25) 78
34.4%

program8
Text

MISSING 

Distinct3
Distinct (%)42.9%
Missing433
Missing (%)98.4%
Memory size14.1 KiB
2023-12-09T22:07:55.504826image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length52
Median length5
Mean length15.14285714
Min length5

Characters and Unicode

Total characters106
Distinct characters27
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)28.6%

Sample

1st rowZoned
2nd rowZoned
3rd rowZoned
4th rowSchool for International Studies/Honors AVID Program
5th rowZoned
ValueCountFrequency (%)
zoned 5
33.3%
institute 1
 
6.7%
of 1
 
6.7%
forensic 1
 
6.7%
science 1
 
6.7%
school 1
 
6.7%
for 1
 
6.7%
international 1
 
6.7%
studies/honors 1
 
6.7%
avid 1
 
6.7%
2023-12-09T22:07:55.814898image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o 14
13.2%
n 12
11.3%
e 11
 
10.4%
8
 
7.5%
r 6
 
5.7%
d 6
 
5.7%
t 6
 
5.7%
i 5
 
4.7%
Z 5
 
4.7%
s 4
 
3.8%
Other values (17) 29
27.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 80
75.5%
Uppercase Letter 17
 
16.0%
Space Separator 8
 
7.5%
Other Punctuation 1
 
0.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 14
17.5%
n 12
15.0%
e 11
13.8%
r 6
7.5%
d 6
7.5%
t 6
7.5%
i 5
 
6.2%
s 4
 
5.0%
c 4
 
5.0%
a 3
 
3.8%
Other values (6) 9
11.2%
Uppercase Letter
ValueCountFrequency (%)
Z 5
29.4%
S 3
17.6%
I 3
17.6%
F 1
 
5.9%
H 1
 
5.9%
A 1
 
5.9%
V 1
 
5.9%
D 1
 
5.9%
P 1
 
5.9%
Space Separator
ValueCountFrequency (%)
8
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 97
91.5%
Common 9
 
8.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 14
14.4%
n 12
12.4%
e 11
11.3%
r 6
 
6.2%
d 6
 
6.2%
t 6
 
6.2%
i 5
 
5.2%
Z 5
 
5.2%
s 4
 
4.1%
c 4
 
4.1%
Other values (15) 24
24.7%
Common
ValueCountFrequency (%)
8
88.9%
/ 1
 
11.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 106
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o 14
13.2%
n 12
11.3%
e 11
 
10.4%
8
 
7.5%
r 6
 
5.7%
d 6
 
5.7%
t 6
 
5.7%
i 5
 
4.7%
Z 5
 
4.7%
s 4
 
3.8%
Other values (17) 29
27.4%

program9
Text

MISSING 

Distinct2
Distinct (%)100.0%
Missing438
Missing (%)99.5%
Memory size13.9 KiB
2023-12-09T22:07:55.979206image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length11
Median length8
Mean length8
Min length5

Characters and Unicode

Total characters16
Distinct characters15
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st rowVisual Arts
2nd rowZoned
ValueCountFrequency (%)
visual 1
33.3%
arts 1
33.3%
zoned 1
33.3%
2023-12-09T22:07:56.267065image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
s 2
 
12.5%
V 1
 
6.2%
i 1
 
6.2%
u 1
 
6.2%
a 1
 
6.2%
l 1
 
6.2%
1
 
6.2%
A 1
 
6.2%
r 1
 
6.2%
t 1
 
6.2%
Other values (5) 5
31.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 12
75.0%
Uppercase Letter 3
 
18.8%
Space Separator 1
 
6.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
s 2
16.7%
i 1
8.3%
u 1
8.3%
a 1
8.3%
l 1
8.3%
r 1
8.3%
t 1
8.3%
o 1
8.3%
n 1
8.3%
e 1
8.3%
Uppercase Letter
ValueCountFrequency (%)
V 1
33.3%
A 1
33.3%
Z 1
33.3%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 15
93.8%
Common 1
 
6.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
s 2
13.3%
V 1
 
6.7%
i 1
 
6.7%
u 1
 
6.7%
a 1
 
6.7%
l 1
 
6.7%
A 1
 
6.7%
r 1
 
6.7%
t 1
 
6.7%
Z 1
 
6.7%
Other values (4) 4
26.7%
Common
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 16
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
s 2
 
12.5%
V 1
 
6.2%
i 1
 
6.2%
u 1
 
6.2%
a 1
 
6.2%
l 1
 
6.2%
1
 
6.2%
A 1
 
6.2%
r 1
 
6.2%
t 1
 
6.2%
Other values (5) 5
31.2%

program10
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing439
Missing (%)99.8%
Memory size13.9 KiB
2023-12-09T22:07:56.420810image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length5
Median length5
Mean length5
Min length5

Characters and Unicode

Total characters5
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowZoned
ValueCountFrequency (%)
zoned 1
100.0%
2023-12-09T22:07:56.703795image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
Z 1
20.0%
o 1
20.0%
n 1
20.0%
e 1
20.0%
d 1
20.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 4
80.0%
Uppercase Letter 1
 
20.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 1
25.0%
n 1
25.0%
e 1
25.0%
d 1
25.0%
Uppercase Letter
ValueCountFrequency (%)
Z 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 5
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
Z 1
20.0%
o 1
20.0%
n 1
20.0%
e 1
20.0%
d 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
Z 1
20.0%
o 1
20.0%
n 1
20.0%
e 1
20.0%
d 1
20.0%

code1
Text

Distinct433
Distinct (%)98.4%
Missing0
Missing (%)0.0%
Memory size26.4 KiB
2023-12-09T22:07:57.213792image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length8
Median length4
Mean length4.063636364
Min length4

Characters and Unicode

Total characters1788
Distinct characters32
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique432 ?
Unique (%)98.2%

Sample

1st rowM64A
2nd rowL72A
3rd rowY01T
4th rowK48A
5th rowQ66A
ValueCountFrequency (%)
no 9
 
2.0%
code 8
 
1.8%
x49b 1
 
0.2%
k08x 1
 
0.2%
q66a 1
 
0.2%
k71b 1
 
0.2%
m17j 1
 
0.2%
q18a 1
 
0.2%
k62x 1
 
0.2%
m44x 1
 
0.2%
Other values (424) 424
94.4%
2023-12-09T22:07:57.832460image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
A 334
18.7%
X 121
 
6.8%
5 105
 
5.9%
3 99
 
5.5%
1 97
 
5.4%
2 96
 
5.4%
4 91
 
5.1%
6 87
 
4.9%
7 85
 
4.8%
M 82
 
4.6%
Other values (22) 591
33.1%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 916
51.2%
Decimal Number 863
48.3%
Space Separator 9
 
0.5%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A 334
36.5%
X 121
 
13.2%
M 82
 
9.0%
Q 79
 
8.6%
K 76
 
8.3%
L 50
 
5.5%
Y 36
 
3.9%
R 34
 
3.7%
B 20
 
2.2%
O 18
 
2.0%
Other values (11) 66
 
7.2%
Decimal Number
ValueCountFrequency (%)
5 105
12.2%
3 99
11.5%
1 97
11.2%
2 96
11.1%
4 91
10.5%
6 87
10.1%
7 85
9.8%
0 69
8.0%
8 67
7.8%
9 67
7.8%
Space Separator
ValueCountFrequency (%)
9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 916
51.2%
Common 872
48.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
A 334
36.5%
X 121
 
13.2%
M 82
 
9.0%
Q 79
 
8.6%
K 76
 
8.3%
L 50
 
5.5%
Y 36
 
3.9%
R 34
 
3.7%
B 20
 
2.2%
O 18
 
2.0%
Other values (11) 66
 
7.2%
Common
ValueCountFrequency (%)
5 105
12.0%
3 99
11.4%
1 97
11.1%
2 96
11.0%
4 91
10.4%
6 87
10.0%
7 85
9.7%
0 69
7.9%
8 67
7.7%
9 67
7.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1788
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
A 334
18.7%
X 121
 
6.8%
5 105
 
5.9%
3 99
 
5.5%
1 97
 
5.4%
2 96
 
5.4%
4 91
 
5.1%
6 87
 
4.9%
7 85
 
4.8%
M 82
 
4.6%
Other values (22) 591
33.1%

code2
Text

MISSING 

Distinct128
Distinct (%)100.0%
Missing312
Missing (%)70.9%
Memory size17.5 KiB
2023-12-09T22:07:58.270394image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length8
Median length4
Mean length4.03125
Min length4

Characters and Unicode

Total characters516
Distinct characters30
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique128 ?
Unique (%)100.0%

Sample

1st rowX95B
2nd rowQ35P
3rd rowQ85F
4th rowQ40J
5th rowX53B
ValueCountFrequency (%)
q82b 1
 
0.8%
q40j 1
 
0.8%
m35b 1
 
0.8%
k06c 1
 
0.8%
q20h 1
 
0.8%
m39b 1
 
0.8%
y31c 1
 
0.8%
r10c 1
 
0.8%
q85f 1
 
0.8%
k51b 1
 
0.8%
Other values (119) 119
92.2%
2023-12-09T22:07:58.852320image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
B 66
 
12.8%
K 47
 
9.1%
1 36
 
7.0%
6 33
 
6.4%
Q 31
 
6.0%
5 31
 
6.0%
2 27
 
5.2%
3 27
 
5.2%
0 25
 
4.8%
M 23
 
4.5%
Other values (20) 170
32.9%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 260
50.4%
Decimal Number 255
49.4%
Space Separator 1
 
0.2%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
B 66
25.4%
K 47
18.1%
Q 31
11.9%
M 23
 
8.8%
X 18
 
6.9%
C 17
 
6.5%
R 10
 
3.8%
L 9
 
3.5%
J 8
 
3.1%
D 8
 
3.1%
Other values (9) 23
 
8.8%
Decimal Number
ValueCountFrequency (%)
1 36
14.1%
6 33
12.9%
5 31
12.2%
2 27
10.6%
3 27
10.6%
0 25
9.8%
7 22
8.6%
8 20
7.8%
4 18
7.1%
9 16
6.3%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 260
50.4%
Common 256
49.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
B 66
25.4%
K 47
18.1%
Q 31
11.9%
M 23
 
8.8%
X 18
 
6.9%
C 17
 
6.5%
R 10
 
3.8%
L 9
 
3.5%
J 8
 
3.1%
D 8
 
3.1%
Other values (9) 23
 
8.8%
Common
ValueCountFrequency (%)
1 36
14.1%
6 33
12.9%
5 31
12.1%
2 27
10.5%
3 27
10.5%
0 25
9.8%
7 22
8.6%
8 20
7.8%
4 18
7.0%
9 16
6.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 516
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
B 66
 
12.8%
K 47
 
9.1%
1 36
 
7.0%
6 33
 
6.4%
Q 31
 
6.0%
5 31
 
6.0%
2 27
 
5.2%
3 27
 
5.2%
0 25
 
4.8%
M 23
 
4.5%
Other values (20) 170
32.9%

code3
Text

MISSING 

Distinct70
Distinct (%)100.0%
Missing370
Missing (%)84.1%
Memory size15.9 KiB
2023-12-09T22:07:59.202130image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length8
Median length4
Mean length4.057142857
Min length4

Characters and Unicode

Total characters284
Distinct characters27
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique70 ?
Unique (%)100.0%

Sample

1st rowQ35Z
2nd rowQ40K
3rd rowM81K
4th rowX49D
5th rowX25D
ValueCountFrequency (%)
m35c 1
 
1.4%
k88c 1
 
1.4%
k70e 1
 
1.4%
k68j 1
 
1.4%
x10j 1
 
1.4%
k24j 1
 
1.4%
x69e 1
 
1.4%
q67m 1
 
1.4%
k11e 1
 
1.4%
q10c 1
 
1.4%
Other values (61) 61
85.9%
2023-12-09T22:07:59.691440image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
K 32
 
11.3%
1 22
 
7.7%
6 20
 
7.0%
Q 19
 
6.7%
C 17
 
6.0%
2 17
 
6.0%
0 15
 
5.3%
M 14
 
4.9%
3 13
 
4.6%
7 12
 
4.2%
Other values (17) 103
36.3%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 144
50.7%
Decimal Number 139
48.9%
Space Separator 1
 
0.4%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
K 32
22.2%
Q 19
13.2%
C 17
11.8%
M 14
9.7%
J 10
 
6.9%
R 10
 
6.9%
D 9
 
6.2%
X 8
 
5.6%
H 5
 
3.5%
L 5
 
3.5%
Other values (6) 15
10.4%
Decimal Number
ValueCountFrequency (%)
1 22
15.8%
6 20
14.4%
2 17
12.2%
0 15
10.8%
3 13
9.4%
7 12
8.6%
8 12
8.6%
4 10
7.2%
5 10
7.2%
9 8
 
5.8%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 144
50.7%
Common 140
49.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
K 32
22.2%
Q 19
13.2%
C 17
11.8%
M 14
9.7%
J 10
 
6.9%
R 10
 
6.9%
D 9
 
6.2%
X 8
 
5.6%
H 5
 
3.5%
L 5
 
3.5%
Other values (6) 15
10.4%
Common
ValueCountFrequency (%)
1 22
15.7%
6 20
14.3%
2 17
12.1%
0 15
10.7%
3 13
9.3%
7 12
8.6%
8 12
8.6%
4 10
7.1%
5 10
7.1%
9 8
 
5.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 284
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
K 32
 
11.3%
1 22
 
7.7%
6 20
 
7.0%
Q 19
 
6.7%
C 17
 
6.0%
2 17
 
6.0%
0 15
 
5.3%
M 14
 
4.9%
3 13
 
4.6%
7 12
 
4.2%
Other values (17) 103
36.3%

code4
Text

MISSING 

Distinct53
Distinct (%)100.0%
Missing387
Missing (%)88.0%
Memory size15.4 KiB
2023-12-09T22:07:59.989912image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length8
Median length4
Mean length4.075471698
Min length4

Characters and Unicode

Total characters216
Distinct characters30
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique53 ?
Unique (%)100.0%

Sample

1st rowQ40L
2nd rowM81N
3rd rowX49E
4th rowX25E
5th rowK78D
ValueCountFrequency (%)
m57e 1
 
1.9%
q18z 1
 
1.9%
x20s 1
 
1.9%
q23j 1
 
1.9%
k78d 1
 
1.9%
k47m 1
 
1.9%
q40l 1
 
1.9%
q34z 1
 
1.9%
k56l 1
 
1.9%
k17s 1
 
1.9%
Other values (44) 44
81.5%
2023-12-09T22:08:00.428059image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
K 27
 
12.5%
1 20
 
9.3%
Q 16
 
7.4%
2 15
 
6.9%
0 12
 
5.6%
6 12
 
5.6%
7 11
 
5.1%
4 10
 
4.6%
8 9
 
4.2%
D 9
 
4.2%
Other values (20) 75
34.7%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 110
50.9%
Decimal Number 105
48.6%
Space Separator 1
 
0.5%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
K 27
24.5%
Q 16
14.5%
D 9
 
8.2%
M 8
 
7.3%
N 7
 
6.4%
R 6
 
5.5%
Z 5
 
4.5%
E 5
 
4.5%
X 5
 
4.5%
J 4
 
3.6%
Other values (9) 18
16.4%
Decimal Number
ValueCountFrequency (%)
1 20
19.0%
2 15
14.3%
0 12
11.4%
6 12
11.4%
7 11
10.5%
4 10
9.5%
8 9
8.6%
9 6
 
5.7%
3 5
 
4.8%
5 5
 
4.8%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 110
50.9%
Common 106
49.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
K 27
24.5%
Q 16
14.5%
D 9
 
8.2%
M 8
 
7.3%
N 7
 
6.4%
R 6
 
5.5%
Z 5
 
4.5%
E 5
 
4.5%
X 5
 
4.5%
J 4
 
3.6%
Other values (9) 18
16.4%
Common
ValueCountFrequency (%)
1 20
18.9%
2 15
14.2%
0 12
11.3%
6 12
11.3%
7 11
10.4%
4 10
9.4%
8 9
8.5%
9 6
 
5.7%
3 5
 
4.7%
5 5
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 216
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
K 27
 
12.5%
1 20
 
9.3%
Q 16
 
7.4%
2 15
 
6.9%
0 12
 
5.6%
6 12
 
5.6%
7 11
 
5.1%
4 10
 
4.6%
8 9
 
4.2%
D 9
 
4.2%
Other values (20) 75
34.7%

code5
Text

MISSING 

Distinct38
Distinct (%)100.0%
Missing402
Missing (%)91.4%
Memory size15.0 KiB
2023-12-09T22:08:00.696607image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length8
Median length4
Mean length4.105263158
Min length4

Characters and Unicode

Total characters156
Distinct characters30
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique38 ?
Unique (%)100.0%

Sample

1st rowQ40M
2nd rowX25F
3rd rowK78F
4th rowQ24L
5th rowQ15Z
ValueCountFrequency (%)
r10l 1
 
2.6%
q40m 1
 
2.6%
q14z 1
 
2.6%
m42p 1
 
2.6%
k47r 1
 
2.6%
k16f 1
 
2.6%
r19e 1
 
2.6%
q16z 1
 
2.6%
q12e 1
 
2.6%
q68o 1
 
2.6%
Other values (29) 29
74.4%
2023-12-09T22:08:01.104483image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
K 15
 
9.6%
Q 14
 
9.0%
1 13
 
8.3%
2 13
 
8.3%
0 10
 
6.4%
6 10
 
6.4%
R 8
 
5.1%
7 8
 
5.1%
4 7
 
4.5%
M 7
 
4.5%
Other values (20) 51
32.7%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 80
51.3%
Decimal Number 75
48.1%
Space Separator 1
 
0.6%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
K 15
18.8%
Q 14
17.5%
R 8
10.0%
M 7
8.8%
E 5
 
6.2%
L 4
 
5.0%
Z 4
 
5.0%
P 3
 
3.8%
F 3
 
3.8%
X 3
 
3.8%
Other values (9) 14
17.5%
Decimal Number
ValueCountFrequency (%)
1 13
17.3%
2 13
17.3%
0 10
13.3%
6 10
13.3%
7 8
10.7%
4 7
9.3%
9 5
 
6.7%
5 5
 
6.7%
8 3
 
4.0%
3 1
 
1.3%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 80
51.3%
Common 76
48.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
K 15
18.8%
Q 14
17.5%
R 8
10.0%
M 7
8.8%
E 5
 
6.2%
L 4
 
5.0%
Z 4
 
5.0%
P 3
 
3.8%
F 3
 
3.8%
X 3
 
3.8%
Other values (9) 14
17.5%
Common
ValueCountFrequency (%)
1 13
17.1%
2 13
17.1%
0 10
13.2%
6 10
13.2%
7 8
10.5%
4 7
9.2%
9 5
 
6.6%
5 5
 
6.6%
8 3
 
3.9%
1
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 156
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
K 15
 
9.6%
Q 14
 
9.0%
1 13
 
8.3%
2 13
 
8.3%
0 10
 
6.4%
6 10
 
6.4%
R 8
 
5.1%
7 8
 
5.1%
4 7
 
4.5%
M 7
 
4.5%
Other values (20) 51
32.7%

code6
Text

MISSING 

Distinct24
Distinct (%)100.0%
Missing416
Missing (%)94.5%
Memory size14.6 KiB
2023-12-09T22:08:01.341901image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length8
Median length4
Mean length4.166666667
Min length4

Characters and Unicode

Total characters100
Distinct characters30
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24 ?
Unique (%)100.0%

Sample

1st rowQ40N
2nd rowX25H
3rd rowK78G
4th rowQ24P
5th rowQ19Z
ValueCountFrequency (%)
k16z 1
 
4.0%
q40n 1
 
4.0%
q10f 1
 
4.0%
r20p 1
 
4.0%
r60p 1
 
4.0%
q12g 1
 
4.0%
q24p 1
 
4.0%
x25h 1
 
4.0%
k28m 1
 
4.0%
k69p 1
 
4.0%
Other values (15) 15
60.0%
2023-12-09T22:08:01.705382image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 9
 
9.0%
K 8
 
8.0%
Q 8
 
8.0%
1 8
 
8.0%
6 7
 
7.0%
R 6
 
6.0%
Z 5
 
5.0%
7 5
 
5.0%
0 5
 
5.0%
9 4
 
4.0%
Other values (20) 35
35.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 52
52.0%
Decimal Number 47
47.0%
Space Separator 1
 
1.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
K 8
15.4%
Q 8
15.4%
R 6
11.5%
Z 5
9.6%
P 4
 
7.7%
M 3
 
5.8%
G 2
 
3.8%
H 2
 
3.8%
N 2
 
3.8%
O 2
 
3.8%
Other values (9) 10
19.2%
Decimal Number
ValueCountFrequency (%)
2 9
19.1%
1 8
17.0%
6 7
14.9%
7 5
10.6%
0 5
10.6%
9 4
8.5%
5 3
 
6.4%
4 3
 
6.4%
8 2
 
4.3%
3 1
 
2.1%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 52
52.0%
Common 48
48.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
K 8
15.4%
Q 8
15.4%
R 6
11.5%
Z 5
9.6%
P 4
 
7.7%
M 3
 
5.8%
G 2
 
3.8%
H 2
 
3.8%
N 2
 
3.8%
O 2
 
3.8%
Other values (9) 10
19.2%
Common
ValueCountFrequency (%)
2 9
18.8%
1 8
16.7%
6 7
14.6%
7 5
10.4%
0 5
10.4%
9 4
8.3%
5 3
 
6.2%
4 3
 
6.2%
8 2
 
4.2%
1
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 100
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 9
 
9.0%
K 8
 
8.0%
Q 8
 
8.0%
1 8
 
8.0%
6 7
 
7.0%
R 6
 
6.0%
Z 5
 
5.0%
7 5
 
5.0%
0 5
 
5.0%
9 4
 
4.0%
Other values (20) 35
35.0%

code7
Text

MISSING 

Distinct14
Distinct (%)100.0%
Missing426
Missing (%)96.8%
Memory size14.3 KiB
2023-12-09T22:08:01.913174image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length4
Median length4
Mean length4
Min length4

Characters and Unicode

Total characters56
Distinct characters20
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique14 ?
Unique (%)100.0%

Sample

1st rowX25Z
2nd rowQ24T
3rd rowR60R
4th rowQ10G
5th rowQ29S
ValueCountFrequency (%)
x25z 1
 
7.1%
k69r 1
 
7.1%
q12z 1
 
7.1%
q10g 1
 
7.1%
k28z 1
 
7.1%
q29s 1
 
7.1%
r10r 1
 
7.1%
r20s 1
 
7.1%
r19g 1
 
7.1%
k57p 1
 
7.1%
Other values (4) 4
28.6%
2023-12-09T22:08:02.238922image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
R 8
14.3%
2 6
10.7%
Q 5
 
8.9%
1 5
 
8.9%
0 4
 
7.1%
Z 3
 
5.4%
K 3
 
5.4%
6 3
 
5.4%
9 3
 
5.4%
7 3
 
5.4%
Other values (10) 13
23.2%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 28
50.0%
Decimal Number 28
50.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
R 8
28.6%
Q 5
17.9%
Z 3
 
10.7%
K 3
 
10.7%
G 2
 
7.1%
S 2
 
7.1%
V 1
 
3.6%
T 1
 
3.6%
X 1
 
3.6%
P 1
 
3.6%
Decimal Number
ValueCountFrequency (%)
2 6
21.4%
1 5
17.9%
0 4
14.3%
6 3
10.7%
9 3
10.7%
7 3
10.7%
5 2
 
7.1%
4 1
 
3.6%
8 1
 
3.6%

Most occurring scripts

ValueCountFrequency (%)
Latin 28
50.0%
Common 28
50.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
R 8
28.6%
Q 5
17.9%
Z 3
 
10.7%
K 3
 
10.7%
G 2
 
7.1%
S 2
 
7.1%
V 1
 
3.6%
T 1
 
3.6%
X 1
 
3.6%
P 1
 
3.6%
Common
ValueCountFrequency (%)
2 6
21.4%
1 5
17.9%
0 4
14.3%
6 3
10.7%
9 3
10.7%
7 3
10.7%
5 2
 
7.1%
4 1
 
3.6%
8 1
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 56
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
R 8
14.3%
2 6
10.7%
Q 5
 
8.9%
1 5
 
8.9%
0 4
 
7.1%
Z 3
 
5.4%
K 3
 
5.4%
6 3
 
5.4%
9 3
 
5.4%
7 3
 
5.4%
Other values (10) 13
23.2%

code8
Text

MISSING 

Distinct7
Distinct (%)100.0%
Missing433
Missing (%)98.4%
Memory size14.1 KiB
2023-12-09T22:08:02.423435image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length4
Median length4
Mean length4
Min length4

Characters and Unicode

Total characters28
Distinct characters11
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7 ?
Unique (%)100.0%

Sample

1st rowQ24Z
2nd rowQ10Z
3rd rowQ29Z
4th rowR19H
5th rowR17Z
ValueCountFrequency (%)
r10z 1
14.3%
r17z 1
14.3%
q29z 1
14.3%
r20t 1
14.3%
r19h 1
14.3%
q24z 1
14.3%
q10z 1
14.3%
2023-12-09T22:08:02.720766image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
Z 5
17.9%
R 4
14.3%
1 4
14.3%
0 3
10.7%
Q 3
10.7%
2 3
10.7%
9 2
 
7.1%
7 1
 
3.6%
T 1
 
3.6%
H 1
 
3.6%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 14
50.0%
Decimal Number 14
50.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 4
28.6%
0 3
21.4%
2 3
21.4%
9 2
14.3%
7 1
 
7.1%
4 1
 
7.1%
Uppercase Letter
ValueCountFrequency (%)
Z 5
35.7%
R 4
28.6%
Q 3
21.4%
T 1
 
7.1%
H 1
 
7.1%

Most occurring scripts

ValueCountFrequency (%)
Latin 14
50.0%
Common 14
50.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 4
28.6%
0 3
21.4%
2 3
21.4%
9 2
14.3%
7 1
 
7.1%
4 1
 
7.1%
Latin
ValueCountFrequency (%)
Z 5
35.7%
R 4
28.6%
Q 3
21.4%
T 1
 
7.1%
H 1
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 28
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
Z 5
17.9%
R 4
14.3%
1 4
14.3%
0 3
10.7%
Q 3
10.7%
2 3
10.7%
9 2
 
7.1%
7 1
 
3.6%
T 1
 
3.6%
H 1
 
3.6%

code9
Text

MISSING 

Distinct2
Distinct (%)100.0%
Missing438
Missing (%)99.5%
Memory size13.9 KiB
2023-12-09T22:08:02.877104image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length4
Median length4
Mean length4
Min length4

Characters and Unicode

Total characters8
Distinct characters7
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st rowR19J
2nd rowR20Z
ValueCountFrequency (%)
r19j 1
50.0%
r20z 1
50.0%
2023-12-09T22:08:03.142687image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
R 2
25.0%
1 1
12.5%
9 1
12.5%
J 1
12.5%
2 1
12.5%
0 1
12.5%
Z 1
12.5%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 4
50.0%
Decimal Number 4
50.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 1
25.0%
9 1
25.0%
2 1
25.0%
0 1
25.0%
Uppercase Letter
ValueCountFrequency (%)
R 2
50.0%
J 1
25.0%
Z 1
25.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 4
50.0%
Common 4
50.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 1
25.0%
9 1
25.0%
2 1
25.0%
0 1
25.0%
Latin
ValueCountFrequency (%)
R 2
50.0%
J 1
25.0%
Z 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
R 2
25.0%
1 1
12.5%
9 1
12.5%
J 1
12.5%
2 1
12.5%
0 1
12.5%
Z 1
12.5%

code10
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing439
Missing (%)99.8%
Memory size13.9 KiB
2023-12-09T22:08:03.273851image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length4
Median length4
Mean length4
Min length4

Characters and Unicode

Total characters4
Distinct characters4
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowR19Z
ValueCountFrequency (%)
r19z 1
100.0%
2023-12-09T22:08:03.512622image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
R 1
25.0%
1 1
25.0%
9 1
25.0%
Z 1
25.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 2
50.0%
Decimal Number 2
50.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
R 1
50.0%
Z 1
50.0%
Decimal Number
ValueCountFrequency (%)
1 1
50.0%
9 1
50.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2
50.0%
Common 2
50.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
R 1
50.0%
Z 1
50.0%
Common
ValueCountFrequency (%)
1 1
50.0%
9 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
R 1
25.0%
1 1
25.0%
9 1
25.0%
Z 1
25.0%

interest1
Text

Distinct20
Distinct (%)4.5%
Missing0
Missing (%)0.0%
Memory size34.5 KiB
2023-12-09T22:08:03.730780image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length35
Median length31
Mean length23.11590909
Min length5

Characters and Unicode

Total characters10171
Distinct characters43
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)0.5%

Sample

1st rowHumanities & Interdisciplinary
2nd rowHumanities & Interdisciplinary
3rd rowScience & Math
4th rowPerforming Arts
5th rowHumanities & Interdisciplinary
ValueCountFrequency (%)
327
26.9%
humanities 211
17.4%
interdisciplinary 211
17.4%
science 77
 
6.3%
math 44
 
3.6%
performing 27
 
2.2%
arts 27
 
2.2%
computer 26
 
2.1%
technology 26
 
2.1%
law 23
 
1.9%
Other values (22) 215
17.7%
2023-12-09T22:08:04.092460image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
i 1329
13.1%
n 963
 
9.5%
e 840
 
8.3%
774
 
7.6%
r 644
 
6.3%
t 624
 
6.1%
s 624
 
6.1%
a 570
 
5.6%
c 415
 
4.1%
& 327
 
3.2%
Other values (33) 3061
30.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 8161
80.2%
Uppercase Letter 897
 
8.8%
Space Separator 774
 
7.6%
Other Punctuation 339
 
3.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i 1329
16.3%
n 963
11.8%
e 840
10.3%
r 644
7.9%
t 624
7.6%
s 624
7.6%
a 570
 
7.0%
c 415
 
5.1%
m 321
 
3.9%
l 305
 
3.7%
Other values (10) 1526
18.7%
Uppercase Letter
ValueCountFrequency (%)
H 237
26.4%
I 211
23.5%
S 77
 
8.6%
A 62
 
6.9%
P 50
 
5.6%
M 44
 
4.9%
C 42
 
4.7%
T 37
 
4.1%
V 27
 
3.0%
G 23
 
2.6%
Other values (9) 87
 
9.7%
Other Punctuation
ValueCountFrequency (%)
& 327
96.5%
/ 9
 
2.7%
, 3
 
0.9%
Space Separator
ValueCountFrequency (%)
774
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 9058
89.1%
Common 1113
 
10.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
i 1329
14.7%
n 963
 
10.6%
e 840
 
9.3%
r 644
 
7.1%
t 624
 
6.9%
s 624
 
6.9%
a 570
 
6.3%
c 415
 
4.6%
m 321
 
3.5%
l 305
 
3.4%
Other values (29) 2423
26.7%
Common
ValueCountFrequency (%)
774
69.5%
& 327
29.4%
/ 9
 
0.8%
, 3
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10171
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
i 1329
13.1%
n 963
 
9.5%
e 840
 
8.3%
774
 
7.6%
r 644
 
6.3%
t 624
 
6.1%
s 624
 
6.1%
a 570
 
5.6%
c 415
 
4.1%
& 327
 
3.2%
Other values (33) 3061
30.1%

interest2
Text

MISSING 

Distinct20
Distinct (%)15.6%
Missing312
Missing (%)70.9%
Memory size19.3 KiB
2023-12-09T22:08:04.308295image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length36
Median length30
Mean length18.7421875
Min length5

Characters and Unicode

Total characters2399
Distinct characters42
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)4.7%

Sample

1st rowLaw & Government
2nd rowLaw & Government
3rd rowScience & Math
4th rowVisual Art & Design
5th rowHumanities & Interdisciplinary
ValueCountFrequency (%)
66
20.5%
science 29
 
9.0%
humanities 22
 
6.8%
interdisciplinary 22
 
6.8%
arts 21
 
6.5%
performing 18
 
5.6%
math 16
 
5.0%
health 11
 
3.4%
professions 11
 
3.4%
computer 10
 
3.1%
Other values (21) 96
29.8%
2023-12-09T22:08:04.681065image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
i 239
 
10.0%
e 226
 
9.4%
n 220
 
9.2%
194
 
8.1%
r 165
 
6.9%
s 146
 
6.1%
t 135
 
5.6%
a 107
 
4.5%
c 99
 
4.1%
o 94
 
3.9%
Other values (32) 774
32.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1874
78.1%
Uppercase Letter 260
 
10.8%
Space Separator 194
 
8.1%
Other Punctuation 71
 
3.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i 239
12.8%
e 226
12.1%
n 220
11.7%
r 165
8.8%
s 146
 
7.8%
t 135
 
7.2%
a 107
 
5.7%
c 99
 
5.3%
o 94
 
5.0%
m 73
 
3.9%
Other values (10) 370
19.7%
Uppercase Letter
ValueCountFrequency (%)
H 35
13.5%
A 34
13.1%
P 29
11.2%
S 29
11.2%
I 22
8.5%
C 19
7.3%
M 16
6.2%
T 16
6.2%
E 12
 
4.6%
V 10
 
3.8%
Other values (8) 38
14.6%
Other Punctuation
ValueCountFrequency (%)
& 66
93.0%
/ 3
 
4.2%
, 2
 
2.8%
Space Separator
ValueCountFrequency (%)
194
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2134
89.0%
Common 265
 
11.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
i 239
 
11.2%
e 226
 
10.6%
n 220
 
10.3%
r 165
 
7.7%
s 146
 
6.8%
t 135
 
6.3%
a 107
 
5.0%
c 99
 
4.6%
o 94
 
4.4%
m 73
 
3.4%
Other values (28) 630
29.5%
Common
ValueCountFrequency (%)
194
73.2%
& 66
 
24.9%
/ 3
 
1.1%
, 2
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2399
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
i 239
 
10.0%
e 226
 
9.4%
n 220
 
9.2%
194
 
8.1%
r 165
 
6.9%
s 146
 
6.1%
t 135
 
5.6%
a 107
 
4.5%
c 99
 
4.1%
o 94
 
3.9%
Other values (32) 774
32.3%

interest3
Text

MISSING 

Distinct18
Distinct (%)25.7%
Missing370
Missing (%)84.1%
Memory size16.8 KiB
2023-12-09T22:08:04.909324image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length35
Median length29
Mean length17.28571429
Min length5

Characters and Unicode

Total characters1210
Distinct characters43
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7 ?
Unique (%)10.0%

Sample

1st rowZoned
2nd rowPerforming Arts
3rd rowPerforming Arts
4th rowPerforming Arts/Visual Art & Design
5th rowCulinary Arts
ValueCountFrequency (%)
30
18.2%
performing 14
 
8.5%
science 14
 
8.5%
arts 12
 
7.3%
engineering 10
 
6.1%
math 8
 
4.8%
humanities 7
 
4.2%
interdisciplinary 7
 
4.2%
art 6
 
3.6%
design 6
 
3.6%
Other values (20) 51
30.9%
2023-12-09T22:08:05.292511image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 121
 
10.0%
n 117
 
9.7%
i 113
 
9.3%
95
 
7.9%
r 91
 
7.5%
s 72
 
6.0%
t 62
 
5.1%
o 55
 
4.5%
g 46
 
3.8%
a 43
 
3.6%
Other values (33) 395
32.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 938
77.5%
Uppercase Letter 142
 
11.7%
Space Separator 95
 
7.9%
Other Punctuation 35
 
2.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 121
12.9%
n 117
12.5%
i 113
12.0%
r 91
9.7%
s 72
7.7%
t 62
 
6.6%
o 55
 
5.9%
g 46
 
4.9%
a 43
 
4.6%
c 41
 
4.4%
Other values (10) 177
18.9%
Uppercase Letter
ValueCountFrequency (%)
A 21
14.8%
P 19
13.4%
S 14
9.9%
H 13
9.2%
E 11
7.7%
C 9
 
6.3%
M 8
 
5.6%
T 8
 
5.6%
I 7
 
4.9%
V 7
 
4.9%
Other values (9) 25
17.6%
Other Punctuation
ValueCountFrequency (%)
& 30
85.7%
/ 4
 
11.4%
, 1
 
2.9%
Space Separator
ValueCountFrequency (%)
95
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1080
89.3%
Common 130
 
10.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 121
 
11.2%
n 117
 
10.8%
i 113
 
10.5%
r 91
 
8.4%
s 72
 
6.7%
t 62
 
5.7%
o 55
 
5.1%
g 46
 
4.3%
a 43
 
4.0%
c 41
 
3.8%
Other values (29) 319
29.5%
Common
ValueCountFrequency (%)
95
73.1%
& 30
 
23.1%
/ 4
 
3.1%
, 1
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1210
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 121
 
10.0%
n 117
 
9.7%
i 113
 
9.3%
95
 
7.9%
r 91
 
7.5%
s 72
 
6.0%
t 62
 
5.1%
o 55
 
4.5%
g 46
 
3.8%
a 43
 
3.6%
Other values (33) 395
32.6%

interest4
Text

MISSING 

Distinct12
Distinct (%)22.6%
Missing387
Missing (%)88.0%
Memory size16.0 KiB
2023-12-09T22:08:05.539570image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length35
Median length29
Mean length16.39622642
Min length5

Characters and Unicode

Total characters869
Distinct characters38
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)3.8%

Sample

1st rowPerforming Arts
2nd rowPerforming Arts
3rd rowPerforming Arts
4th rowCommunications
5th rowHumanities & Interdisciplinary
ValueCountFrequency (%)
20
16.4%
performing 15
12.3%
arts 13
10.7%
science 8
 
6.6%
art 7
 
5.7%
design 7
 
5.7%
engineering 6
 
4.9%
math 6
 
4.9%
professions 5
 
4.1%
health 5
 
4.1%
Other values (11) 30
24.6%
2023-12-09T22:08:05.905176image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
i 81
 
9.3%
n 81
 
9.3%
e 80
 
9.2%
r 74
 
8.5%
69
 
7.9%
s 58
 
6.7%
t 47
 
5.4%
o 43
 
4.9%
g 36
 
4.1%
a 30
 
3.5%
Other values (28) 270
31.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 674
77.6%
Uppercase Letter 104
 
12.0%
Space Separator 69
 
7.9%
Other Punctuation 22
 
2.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i 81
12.0%
n 81
12.0%
e 80
11.9%
r 74
11.0%
s 58
8.6%
t 47
7.0%
o 43
 
6.4%
g 36
 
5.3%
a 30
 
4.5%
m 28
 
4.2%
Other values (10) 116
17.2%
Uppercase Letter
ValueCountFrequency (%)
A 22
21.2%
P 20
19.2%
H 9
8.7%
S 8
 
7.7%
D 7
 
6.7%
V 7
 
6.7%
M 6
 
5.8%
E 6
 
5.8%
Z 5
 
4.8%
C 5
 
4.8%
Other values (5) 9
8.7%
Other Punctuation
ValueCountFrequency (%)
& 20
90.9%
/ 2
 
9.1%
Space Separator
ValueCountFrequency (%)
69
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 778
89.5%
Common 91
 
10.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
i 81
 
10.4%
n 81
 
10.4%
e 80
 
10.3%
r 74
 
9.5%
s 58
 
7.5%
t 47
 
6.0%
o 43
 
5.5%
g 36
 
4.6%
a 30
 
3.9%
m 28
 
3.6%
Other values (25) 220
28.3%
Common
ValueCountFrequency (%)
69
75.8%
& 20
 
22.0%
/ 2
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 869
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
i 81
 
9.3%
n 81
 
9.3%
e 80
 
9.2%
r 74
 
8.5%
69
 
7.9%
s 58
 
6.7%
t 47
 
5.4%
o 43
 
4.9%
g 36
 
4.1%
a 30
 
3.5%
Other values (28) 270
31.1%

interest5
Text

MISSING 

Distinct14
Distinct (%)36.8%
Missing402
Missing (%)91.4%
Memory size15.4 KiB
2023-12-09T22:08:06.145235image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length35
Median length29
Mean length16.78947368
Min length5

Characters and Unicode

Total characters638
Distinct characters41
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)10.5%

Sample

1st rowPerforming Arts
2nd rowJROTC
3rd rowHealth Professions
4th rowPerforming Arts
5th rowZoned
ValueCountFrequency (%)
13
15.5%
performing 12
14.3%
arts 10
11.9%
zoned 4
 
4.8%
humanities 4
 
4.8%
interdisciplinary 4
 
4.8%
science 4
 
4.8%
engineering 3
 
3.6%
computer 3
 
3.6%
technology 3
 
3.6%
Other values (13) 24
28.6%
2023-12-09T22:08:06.531858image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
n 58
 
9.1%
r 57
 
8.9%
e 57
 
8.9%
i 55
 
8.6%
46
 
7.2%
o 38
 
6.0%
s 38
 
6.0%
t 34
 
5.3%
m 26
 
4.1%
g 25
 
3.9%
Other values (31) 204
32.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 496
77.7%
Uppercase Letter 81
 
12.7%
Space Separator 46
 
7.2%
Other Punctuation 15
 
2.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n 58
11.7%
r 57
11.5%
e 57
11.5%
i 55
11.1%
o 38
7.7%
s 38
7.7%
t 34
 
6.9%
m 26
 
5.2%
g 25
 
5.0%
a 18
 
3.6%
Other values (10) 90
18.1%
Uppercase Letter
ValueCountFrequency (%)
A 15
18.5%
P 14
17.3%
C 8
9.9%
H 6
 
7.4%
T 5
 
6.2%
S 4
 
4.9%
I 4
 
4.9%
Z 4
 
4.9%
E 3
 
3.7%
V 3
 
3.7%
Other values (8) 15
18.5%
Other Punctuation
ValueCountFrequency (%)
& 13
86.7%
/ 2
 
13.3%
Space Separator
ValueCountFrequency (%)
46
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 577
90.4%
Common 61
 
9.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
n 58
 
10.1%
r 57
 
9.9%
e 57
 
9.9%
i 55
 
9.5%
o 38
 
6.6%
s 38
 
6.6%
t 34
 
5.9%
m 26
 
4.5%
g 25
 
4.3%
a 18
 
3.1%
Other values (28) 171
29.6%
Common
ValueCountFrequency (%)
46
75.4%
& 13
 
21.3%
/ 2
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 638
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n 58
 
9.1%
r 57
 
8.9%
e 57
 
8.9%
i 55
 
8.6%
46
 
7.2%
o 38
 
6.0%
s 38
 
6.0%
t 34
 
5.3%
m 26
 
4.1%
g 25
 
3.9%
Other values (31) 204
32.0%

interest6
Text

MISSING 

Distinct11
Distinct (%)45.8%
Missing416
Missing (%)94.5%
Memory size14.9 KiB
2023-12-09T22:08:06.741676image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length35
Median length29.5
Mean length17.5
Min length5

Characters and Unicode

Total characters420
Distinct characters38
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)20.8%

Sample

1st rowPerforming Arts
2nd rowEngineering
3rd rowComputer Science & Technology
4th rowLaw & Government
5th rowZoned
ValueCountFrequency (%)
9
15.3%
zoned 5
 
8.5%
science 4
 
6.8%
technology 4
 
6.8%
computer 4
 
6.8%
performing 4
 
6.8%
arts 3
 
5.1%
art 3
 
5.1%
design 3
 
5.1%
professions 3
 
5.1%
Other values (13) 17
28.8%
2023-12-09T22:08:07.094157image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 44
 
10.5%
n 36
 
8.6%
35
 
8.3%
o 30
 
7.1%
i 30
 
7.1%
r 29
 
6.9%
s 26
 
6.2%
t 19
 
4.5%
g 15
 
3.6%
c 13
 
3.1%
Other values (28) 143
34.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 324
77.1%
Uppercase Letter 50
 
11.9%
Space Separator 35
 
8.3%
Other Punctuation 11
 
2.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 44
13.6%
n 36
11.1%
o 30
9.3%
i 30
9.3%
r 29
9.0%
s 26
 
8.0%
t 19
 
5.9%
g 15
 
4.6%
c 13
 
4.0%
l 13
 
4.0%
Other values (10) 69
21.3%
Uppercase Letter
ValueCountFrequency (%)
P 7
14.0%
A 7
14.0%
T 6
12.0%
Z 5
10.0%
H 5
10.0%
S 4
8.0%
C 4
8.0%
V 3
6.0%
D 3
6.0%
E 2
 
4.0%
Other values (4) 4
8.0%
Other Punctuation
ValueCountFrequency (%)
& 9
81.8%
, 1
 
9.1%
/ 1
 
9.1%
Space Separator
ValueCountFrequency (%)
35
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 374
89.0%
Common 46
 
11.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 44
 
11.8%
n 36
 
9.6%
o 30
 
8.0%
i 30
 
8.0%
r 29
 
7.8%
s 26
 
7.0%
t 19
 
5.1%
g 15
 
4.0%
c 13
 
3.5%
l 13
 
3.5%
Other values (24) 119
31.8%
Common
ValueCountFrequency (%)
35
76.1%
& 9
 
19.6%
, 1
 
2.2%
/ 1
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 420
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 44
 
10.5%
n 36
 
8.6%
35
 
8.3%
o 30
 
7.1%
i 30
 
7.1%
r 29
 
6.9%
s 26
 
6.2%
t 19
 
4.5%
g 15
 
3.6%
c 13
 
3.1%
Other values (28) 143
34.0%

interest7
Text

MISSING 

Distinct8
Distinct (%)57.1%
Missing426
Missing (%)96.8%
Memory size14.4 KiB
2023-12-09T22:08:07.302557image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length30
Median length23.5
Mean length15.42857143
Min length5

Characters and Unicode

Total characters216
Distinct characters30
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)35.7%

Sample

1st rowZoned
2nd rowBusiness
3rd rowArchitecture
4th rowPerforming Arts
5th rowHumanities & Interdisciplinary
ValueCountFrequency (%)
performing 4
14.3%
arts 4
14.3%
4
14.3%
zoned 3
10.7%
humanities 2
7.1%
interdisciplinary 2
7.1%
science 2
7.1%
architecture 1
 
3.6%
health 1
 
3.6%
professions 1
 
3.6%
Other values (4) 4
14.3%
2023-12-09T22:08:07.640266image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 22
 
10.2%
r 20
 
9.3%
i 19
 
8.8%
n 18
 
8.3%
14
 
6.5%
s 14
 
6.5%
t 13
 
6.0%
o 12
 
5.6%
c 9
 
4.2%
m 7
 
3.2%
Other values (20) 68
31.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 174
80.6%
Uppercase Letter 24
 
11.1%
Space Separator 14
 
6.5%
Other Punctuation 4
 
1.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 22
12.6%
r 20
11.5%
i 19
10.9%
n 18
10.3%
s 14
8.0%
t 13
 
7.5%
o 12
 
6.9%
c 9
 
5.2%
m 7
 
4.0%
a 6
 
3.4%
Other values (8) 34
19.5%
Uppercase Letter
ValueCountFrequency (%)
P 5
20.8%
A 5
20.8%
H 3
12.5%
Z 3
12.5%
I 2
 
8.3%
S 2
 
8.3%
M 1
 
4.2%
C 1
 
4.2%
T 1
 
4.2%
B 1
 
4.2%
Space Separator
ValueCountFrequency (%)
14
100.0%
Other Punctuation
ValueCountFrequency (%)
& 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 198
91.7%
Common 18
 
8.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 22
 
11.1%
r 20
 
10.1%
i 19
 
9.6%
n 18
 
9.1%
s 14
 
7.1%
t 13
 
6.6%
o 12
 
6.1%
c 9
 
4.5%
m 7
 
3.5%
a 6
 
3.0%
Other values (18) 58
29.3%
Common
ValueCountFrequency (%)
14
77.8%
& 4
 
22.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 216
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 22
 
10.2%
r 20
 
9.3%
i 19
 
8.8%
n 18
 
8.3%
14
 
6.5%
s 14
 
6.5%
t 13
 
6.0%
o 12
 
5.6%
c 9
 
4.2%
m 7
 
3.2%
Other values (20) 68
31.5%

interest8
Text

MISSING 

Distinct3
Distinct (%)42.9%
Missing433
Missing (%)98.4%
Memory size14.1 KiB
2023-12-09T22:08:07.806730image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length30
Median length5
Mean length9.857142857
Min length5

Characters and Unicode

Total characters69
Distinct characters23
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)28.6%

Sample

1st rowZoned
2nd rowZoned
3rd rowZoned
4th rowHumanities & Interdisciplinary
5th rowZoned
ValueCountFrequency (%)
zoned 5
45.5%
2
 
18.2%
humanities 1
 
9.1%
interdisciplinary 1
 
9.1%
science 1
 
9.1%
math 1
 
9.1%
2023-12-09T22:08:08.096742image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
n 9
13.0%
e 9
13.0%
d 6
 
8.7%
i 6
 
8.7%
Z 5
 
7.2%
o 5
 
7.2%
4
 
5.8%
c 3
 
4.3%
a 3
 
4.3%
t 3
 
4.3%
Other values (13) 16
23.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 54
78.3%
Uppercase Letter 9
 
13.0%
Space Separator 4
 
5.8%
Other Punctuation 2
 
2.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n 9
16.7%
e 9
16.7%
d 6
11.1%
i 6
11.1%
o 5
9.3%
c 3
 
5.6%
a 3
 
5.6%
t 3
 
5.6%
r 2
 
3.7%
s 2
 
3.7%
Other values (6) 6
11.1%
Uppercase Letter
ValueCountFrequency (%)
Z 5
55.6%
I 1
 
11.1%
H 1
 
11.1%
S 1
 
11.1%
M 1
 
11.1%
Space Separator
ValueCountFrequency (%)
4
100.0%
Other Punctuation
ValueCountFrequency (%)
& 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 63
91.3%
Common 6
 
8.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
n 9
14.3%
e 9
14.3%
d 6
9.5%
i 6
9.5%
Z 5
7.9%
o 5
7.9%
c 3
 
4.8%
a 3
 
4.8%
t 3
 
4.8%
r 2
 
3.2%
Other values (11) 12
19.0%
Common
ValueCountFrequency (%)
4
66.7%
& 2
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 69
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n 9
13.0%
e 9
13.0%
d 6
 
8.7%
i 6
 
8.7%
Z 5
 
7.2%
o 5
 
7.2%
4
 
5.8%
c 3
 
4.3%
a 3
 
4.3%
t 3
 
4.3%
Other values (13) 16
23.2%

interest9
Text

MISSING 

Distinct2
Distinct (%)100.0%
Missing438
Missing (%)99.5%
Memory size13.9 KiB
2023-12-09T22:08:08.272894image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length19
Median length12
Mean length12
Min length5

Characters and Unicode

Total characters24
Distinct characters18
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st rowVisual Art & Design
2nd rowZoned
ValueCountFrequency (%)
visual 1
20.0%
art 1
20.0%
1
20.0%
design 1
20.0%
zoned 1
20.0%
2023-12-09T22:08:08.575046image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3
 
12.5%
s 2
 
8.3%
n 2
 
8.3%
e 2
 
8.3%
i 2
 
8.3%
V 1
 
4.2%
D 1
 
4.2%
o 1
 
4.2%
Z 1
 
4.2%
g 1
 
4.2%
Other values (8) 8
33.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 16
66.7%
Uppercase Letter 4
 
16.7%
Space Separator 3
 
12.5%
Other Punctuation 1
 
4.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
s 2
12.5%
n 2
12.5%
e 2
12.5%
i 2
12.5%
o 1
6.2%
g 1
6.2%
t 1
6.2%
r 1
6.2%
l 1
6.2%
a 1
6.2%
Other values (2) 2
12.5%
Uppercase Letter
ValueCountFrequency (%)
V 1
25.0%
D 1
25.0%
Z 1
25.0%
A 1
25.0%
Space Separator
ValueCountFrequency (%)
3
100.0%
Other Punctuation
ValueCountFrequency (%)
& 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 20
83.3%
Common 4
 
16.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
s 2
 
10.0%
n 2
 
10.0%
e 2
 
10.0%
i 2
 
10.0%
V 1
 
5.0%
D 1
 
5.0%
o 1
 
5.0%
Z 1
 
5.0%
g 1
 
5.0%
t 1
 
5.0%
Other values (6) 6
30.0%
Common
ValueCountFrequency (%)
3
75.0%
& 1
 
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 24
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3
 
12.5%
s 2
 
8.3%
n 2
 
8.3%
e 2
 
8.3%
i 2
 
8.3%
V 1
 
4.2%
D 1
 
4.2%
o 1
 
4.2%
Z 1
 
4.2%
g 1
 
4.2%
Other values (8) 8
33.3%

interest10
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing439
Missing (%)99.8%
Memory size13.9 KiB
2023-12-09T22:08:08.718336image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length5
Median length5
Mean length5
Min length5

Characters and Unicode

Total characters5
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowZoned
ValueCountFrequency (%)
zoned 1
100.0%
2023-12-09T22:08:08.967669image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
Z 1
20.0%
o 1
20.0%
n 1
20.0%
e 1
20.0%
d 1
20.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 4
80.0%
Uppercase Letter 1
 
20.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 1
25.0%
n 1
25.0%
e 1
25.0%
d 1
25.0%
Uppercase Letter
ValueCountFrequency (%)
Z 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 5
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
Z 1
20.0%
o 1
20.0%
n 1
20.0%
e 1
20.0%
d 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
Z 1
20.0%
o 1
20.0%
n 1
20.0%
e 1
20.0%
d 1
20.0%

method1
Text

Distinct10
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size30.5 KiB
2023-12-09T22:08:09.159831image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length30
Median length18
Mean length13.67272727
Min length4

Characters and Unicode

Total characters6016
Distinct characters33
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)0.5%

Sample

1st rowScreened
2nd rowLimited Unscreened
3rd rowLimited Unscreened
4th rowEd. Opt.
5th rowLimited Unscreened
ValueCountFrequency (%)
unscreened 220
28.1%
limited 216
27.6%
screened 105
13.4%
ed 87
 
11.1%
opt 87
 
11.1%
language 30
 
3.8%
audition 18
 
2.3%
test 8
 
1.0%
3
 
0.4%
academics 3
 
0.4%
Other values (6) 6
 
0.8%
2023-12-09T22:08:09.492449image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 1234
20.5%
d 651
10.8%
n 597
9.9%
i 475
 
7.9%
343
 
5.7%
t 332
 
5.5%
c 331
 
5.5%
r 330
 
5.5%
L 246
 
4.1%
s 232
 
3.9%
Other values (23) 1245
20.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 4686
77.9%
Uppercase Letter 779
 
12.9%
Space Separator 343
 
5.7%
Other Punctuation 207
 
3.4%
Decimal Number 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 1234
26.3%
d 651
13.9%
n 597
12.7%
i 475
 
10.1%
t 332
 
7.1%
c 331
 
7.1%
r 330
 
7.0%
s 232
 
5.0%
m 219
 
4.7%
p 87
 
1.9%
Other values (6) 198
 
4.2%
Uppercase Letter
ValueCountFrequency (%)
L 246
31.6%
U 220
28.2%
S 105
13.5%
O 87
 
11.2%
E 87
 
11.2%
A 21
 
2.7%
T 8
 
1.0%
Z 1
 
0.1%
P 1
 
0.1%
F 1
 
0.1%
Other values (2) 2
 
0.3%
Other Punctuation
ValueCountFrequency (%)
. 174
84.1%
: 30
 
14.5%
& 3
 
1.4%
Space Separator
ValueCountFrequency (%)
343
100.0%
Decimal Number
ValueCountFrequency (%)
8 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 5465
90.8%
Common 551
 
9.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 1234
22.6%
d 651
11.9%
n 597
10.9%
i 475
 
8.7%
t 332
 
6.1%
c 331
 
6.1%
r 330
 
6.0%
L 246
 
4.5%
s 232
 
4.2%
U 220
 
4.0%
Other values (18) 817
14.9%
Common
ValueCountFrequency (%)
343
62.3%
. 174
31.6%
: 30
 
5.4%
& 3
 
0.5%
8 1
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6016
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 1234
20.5%
d 651
10.8%
n 597
9.9%
i 475
 
7.9%
343
 
5.7%
t 332
 
5.5%
c 331
 
5.5%
r 330
 
5.5%
L 246
 
4.1%
s 232
 
3.9%
Other values (23) 1245
20.7%

method2
Text

MISSING 

Distinct8
Distinct (%)6.2%
Missing312
Missing (%)70.9%
Memory size18.6 KiB
2023-12-09T22:08:09.689980image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length30
Median length8
Mean length12.515625
Min length8

Characters and Unicode

Total characters1602
Distinct characters29
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowFor Continuing 8th Graders
2nd rowScreened
3rd rowLimited Unscreened
4th rowAudition
5th rowEd. Opt.
ValueCountFrequency (%)
screened 42
18.1%
ed 33
14.2%
opt 33
14.2%
unscreened 27
11.6%
limited 25
10.8%
audition 16
 
6.9%
language 12
 
5.2%
for 10
 
4.3%
continuing 10
 
4.3%
8th 10
 
4.3%
Other values (3) 14
 
6.0%
2023-12-09T22:08:10.013127image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 256
16.0%
d 155
 
9.7%
n 154
 
9.6%
104
 
6.5%
i 104
 
6.5%
r 99
 
6.2%
t 94
 
5.9%
c 73
 
4.6%
. 66
 
4.1%
S 42
 
2.6%
Other values (19) 455
28.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1188
74.2%
Uppercase Letter 220
 
13.7%
Space Separator 104
 
6.5%
Other Punctuation 80
 
5.0%
Decimal Number 10
 
0.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 256
21.5%
d 155
13.0%
n 154
13.0%
i 104
8.8%
r 99
 
8.3%
t 94
 
7.9%
c 73
 
6.1%
s 39
 
3.3%
u 38
 
3.2%
o 36
 
3.0%
Other values (5) 140
11.8%
Uppercase Letter
ValueCountFrequency (%)
S 42
19.1%
L 37
16.8%
O 33
15.0%
E 33
15.0%
U 27
12.3%
A 18
8.2%
F 10
 
4.5%
C 10
 
4.5%
G 10
 
4.5%
Other Punctuation
ValueCountFrequency (%)
. 66
82.5%
: 12
 
15.0%
& 2
 
2.5%
Space Separator
ValueCountFrequency (%)
104
100.0%
Decimal Number
ValueCountFrequency (%)
8 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1408
87.9%
Common 194
 
12.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 256
18.2%
d 155
11.0%
n 154
10.9%
i 104
 
7.4%
r 99
 
7.0%
t 94
 
6.7%
c 73
 
5.2%
S 42
 
3.0%
s 39
 
2.8%
u 38
 
2.7%
Other values (14) 354
25.1%
Common
ValueCountFrequency (%)
104
53.6%
. 66
34.0%
: 12
 
6.2%
8 10
 
5.2%
& 2
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1602
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 256
16.0%
d 155
 
9.7%
n 154
 
9.6%
104
 
6.5%
i 104
 
6.5%
r 99
 
6.2%
t 94
 
5.9%
c 73
 
4.6%
. 66
 
4.1%
S 42
 
2.6%
Other values (19) 455
28.4%

method3
Text

MISSING 

Distinct9
Distinct (%)12.9%
Missing370
Missing (%)84.1%
Memory size16.3 KiB
2023-12-09T22:08:10.212233image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length30
Median length8
Mean length9.985714286
Min length8

Characters and Unicode

Total characters699
Distinct characters32
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)4.3%

Sample

1st rowZoned Priority
2nd rowAudition
3rd rowAudition
4th rowEd. Opt.
5th rowEd. Opt.
ValueCountFrequency (%)
screened 27
25.2%
ed 20
18.7%
opt 20
18.7%
audition 14
13.1%
limited 5
 
4.7%
unscreened 5
 
4.7%
language 4
 
3.7%
zoned 3
 
2.8%
priority 2
 
1.9%
guarantee 1
 
0.9%
Other values (6) 6
 
5.6%
2023-12-09T22:08:10.544310image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 112
16.0%
d 76
10.9%
n 62
 
8.9%
i 45
 
6.4%
t 44
 
6.3%
r 40
 
5.7%
. 40
 
5.7%
37
 
5.3%
c 34
 
4.9%
S 27
 
3.9%
Other values (22) 182
26.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 511
73.1%
Uppercase Letter 105
 
15.0%
Other Punctuation 45
 
6.4%
Space Separator 37
 
5.3%
Decimal Number 1
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 112
21.9%
d 76
14.9%
n 62
12.1%
i 45
8.8%
t 44
 
8.6%
r 40
 
7.8%
c 34
 
6.7%
o 21
 
4.1%
u 20
 
3.9%
p 20
 
3.9%
Other values (6) 37
 
7.2%
Uppercase Letter
ValueCountFrequency (%)
S 27
25.7%
O 20
19.0%
E 20
19.0%
A 15
14.3%
L 9
 
8.6%
U 5
 
4.8%
Z 3
 
2.9%
P 2
 
1.9%
G 2
 
1.9%
F 1
 
1.0%
Other Punctuation
ValueCountFrequency (%)
. 40
88.9%
: 4
 
8.9%
& 1
 
2.2%
Space Separator
ValueCountFrequency (%)
37
100.0%
Decimal Number
ValueCountFrequency (%)
8 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 616
88.1%
Common 83
 
11.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 112
18.2%
d 76
12.3%
n 62
10.1%
i 45
 
7.3%
t 44
 
7.1%
r 40
 
6.5%
c 34
 
5.5%
S 27
 
4.4%
o 21
 
3.4%
u 20
 
3.2%
Other values (17) 135
21.9%
Common
ValueCountFrequency (%)
. 40
48.2%
37
44.6%
: 4
 
4.8%
8 1
 
1.2%
& 1
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 699
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 112
16.0%
d 76
10.9%
n 62
 
8.9%
i 45
 
6.4%
t 44
 
6.3%
r 40
 
5.7%
. 40
 
5.7%
37
 
5.3%
c 34
 
4.9%
S 27
 
3.9%
Other values (22) 182
26.0%

method4
Text

MISSING 

Distinct8
Distinct (%)15.1%
Missing387
Missing (%)88.0%
Memory size15.7 KiB
2023-12-09T22:08:10.736666image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length30
Median length8
Mean length10.41509434
Min length8

Characters and Unicode

Total characters552
Distinct characters28
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)1.9%

Sample

1st rowAudition
2nd rowAudition
3rd rowEd. Opt.
4th rowLimited Unscreened
5th rowScreened
ValueCountFrequency (%)
screened 18
22.5%
audition 13
16.2%
ed 11
13.8%
opt 11
13.8%
unscreened 6
 
7.5%
limited 5
 
6.2%
zoned 5
 
6.2%
priority 3
 
3.8%
guarantee 2
 
2.5%
language 2
 
2.5%
Other values (2) 4
 
5.0%
2023-12-09T22:08:11.048667image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 90
16.3%
d 60
10.9%
n 52
 
9.4%
i 44
 
8.0%
t 34
 
6.2%
r 32
 
5.8%
c 28
 
5.1%
27
 
4.9%
. 22
 
4.0%
o 21
 
3.8%
Other values (18) 142
25.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 421
76.3%
Uppercase Letter 78
 
14.1%
Space Separator 27
 
4.9%
Other Punctuation 26
 
4.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 90
21.4%
d 60
14.3%
n 52
12.4%
i 44
10.5%
t 34
 
8.1%
r 32
 
7.6%
c 28
 
6.7%
o 21
 
5.0%
u 17
 
4.0%
p 11
 
2.6%
Other values (5) 32
 
7.6%
Uppercase Letter
ValueCountFrequency (%)
S 18
23.1%
A 15
19.2%
O 11
14.1%
E 11
14.1%
L 7
 
9.0%
U 6
 
7.7%
Z 5
 
6.4%
P 3
 
3.8%
G 2
 
2.6%
Other Punctuation
ValueCountFrequency (%)
. 22
84.6%
: 2
 
7.7%
& 2
 
7.7%
Space Separator
ValueCountFrequency (%)
27
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 499
90.4%
Common 53
 
9.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 90
18.0%
d 60
12.0%
n 52
10.4%
i 44
8.8%
t 34
 
6.8%
r 32
 
6.4%
c 28
 
5.6%
o 21
 
4.2%
S 18
 
3.6%
u 17
 
3.4%
Other values (14) 103
20.6%
Common
ValueCountFrequency (%)
27
50.9%
. 22
41.5%
: 2
 
3.8%
& 2
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 552
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 90
16.3%
d 60
10.9%
n 52
 
9.4%
i 44
 
8.0%
t 34
 
6.2%
r 32
 
5.8%
c 28
 
5.1%
27
 
4.9%
. 22
 
4.0%
o 21
 
3.8%
Other values (18) 142
25.7%

method5
Text

MISSING 

Distinct6
Distinct (%)15.8%
Missing402
Missing (%)91.4%
Memory size15.1 KiB
2023-12-09T22:08:11.240424image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length18
Median length8
Mean length9.263157895
Min length8

Characters and Unicode

Total characters352
Distinct characters25
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)5.3%

Sample

1st rowAudition
2nd rowScreened
3rd rowEd. Opt.
4th rowAudition
5th rowZoned Guarantee
ValueCountFrequency (%)
ed 13
22.8%
opt 13
22.8%
audition 12
21.1%
screened 8
14.0%
zoned 4
 
7.0%
guarantee 4
 
7.0%
language 1
 
1.8%
limited 1
 
1.8%
unscreened 1
 
1.8%
2023-12-09T22:08:11.550841image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 41
11.6%
d 39
11.1%
n 31
 
8.8%
t 30
 
8.5%
. 26
 
7.4%
i 26
 
7.4%
19
 
5.4%
u 17
 
4.8%
o 16
 
4.5%
E 13
 
3.7%
Other values (15) 94
26.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 249
70.7%
Uppercase Letter 57
 
16.2%
Other Punctuation 27
 
7.7%
Space Separator 19
 
5.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 41
16.5%
d 39
15.7%
n 31
12.4%
t 30
12.0%
i 26
10.4%
u 17
6.8%
o 16
 
6.4%
p 13
 
5.2%
r 13
 
5.2%
a 10
 
4.0%
Other values (4) 13
 
5.2%
Uppercase Letter
ValueCountFrequency (%)
E 13
22.8%
O 13
22.8%
A 12
21.1%
S 8
14.0%
G 4
 
7.0%
Z 4
 
7.0%
L 2
 
3.5%
U 1
 
1.8%
Other Punctuation
ValueCountFrequency (%)
. 26
96.3%
: 1
 
3.7%
Space Separator
ValueCountFrequency (%)
19
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 306
86.9%
Common 46
 
13.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 41
13.4%
d 39
12.7%
n 31
10.1%
t 30
9.8%
i 26
 
8.5%
u 17
 
5.6%
o 16
 
5.2%
E 13
 
4.2%
O 13
 
4.2%
p 13
 
4.2%
Other values (12) 67
21.9%
Common
ValueCountFrequency (%)
. 26
56.5%
19
41.3%
: 1
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 352
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 41
11.6%
d 39
11.1%
n 31
 
8.8%
t 30
 
8.5%
. 26
 
7.4%
i 26
 
7.4%
19
 
5.4%
u 17
 
4.8%
o 16
 
4.5%
E 13
 
3.7%
Other values (15) 94
26.7%

method6
Text

MISSING 

Distinct5
Distinct (%)20.8%
Missing416
Missing (%)94.5%
Memory size14.7 KiB
2023-12-09T22:08:12.670323image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length18
Median length8
Mean length10.29166667
Min length8

Characters and Unicode

Total characters247
Distinct characters23
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowAudition
2nd rowScreened
3rd rowScreened
4th rowEd. Opt.
5th rowZoned Guarantee
ValueCountFrequency (%)
ed 8
20.5%
opt 8
20.5%
zoned 5
12.8%
guarantee 5
12.8%
screened 5
12.8%
audition 4
10.3%
limited 2
 
5.1%
unscreened 2
 
5.1%
2023-12-09T22:08:13.007629image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 38
15.4%
d 26
 
10.5%
n 23
 
9.3%
t 19
 
7.7%
. 16
 
6.5%
15
 
6.1%
i 12
 
4.9%
r 12
 
4.9%
a 10
 
4.0%
o 9
 
3.6%
Other values (13) 67
27.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 177
71.7%
Uppercase Letter 39
 
15.8%
Other Punctuation 16
 
6.5%
Space Separator 15
 
6.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 38
21.5%
d 26
14.7%
n 23
13.0%
t 19
10.7%
i 12
 
6.8%
r 12
 
6.8%
a 10
 
5.6%
o 9
 
5.1%
u 9
 
5.1%
p 8
 
4.5%
Other values (3) 11
 
6.2%
Uppercase Letter
ValueCountFrequency (%)
E 8
20.5%
O 8
20.5%
G 5
12.8%
S 5
12.8%
Z 5
12.8%
A 4
10.3%
L 2
 
5.1%
U 2
 
5.1%
Other Punctuation
ValueCountFrequency (%)
. 16
100.0%
Space Separator
ValueCountFrequency (%)
15
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 216
87.4%
Common 31
 
12.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 38
17.6%
d 26
12.0%
n 23
10.6%
t 19
 
8.8%
i 12
 
5.6%
r 12
 
5.6%
a 10
 
4.6%
o 9
 
4.2%
u 9
 
4.2%
E 8
 
3.7%
Other values (11) 50
23.1%
Common
ValueCountFrequency (%)
. 16
51.6%
15
48.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 247
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 38
15.4%
d 26
 
10.5%
n 23
 
9.3%
t 19
 
7.7%
. 16
 
6.5%
15
 
6.1%
i 12
 
4.9%
r 12
 
4.9%
a 10
 
4.0%
o 9
 
3.6%
Other values (13) 67
27.1%

method7
Text

MISSING 

Distinct7
Distinct (%)50.0%
Missing426
Missing (%)96.8%
Memory size14.4 KiB
2023-12-09T22:08:13.215618image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length18
Median length8
Mean length11.07142857
Min length8

Characters and Unicode

Total characters155
Distinct characters25
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)21.4%

Sample

1st rowZoned Guarantee
2nd rowEd. Opt.
3rd rowEd. Opt.
4th rowScreened
5th rowScreened: Language
ValueCountFrequency (%)
screened 5
23.8%
zoned 3
14.3%
guarantee 3
14.3%
ed 2
 
9.5%
opt 2
 
9.5%
audition 2
 
9.5%
unscreened 2
 
9.5%
language 1
 
4.8%
limited 1
 
4.8%
2023-12-09T22:08:13.516794image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 32
20.6%
n 18
11.6%
d 15
 
9.7%
r 10
 
6.5%
t 8
 
5.2%
a 8
 
5.2%
c 7
 
4.5%
7
 
4.5%
u 6
 
3.9%
i 6
 
3.9%
Other values (15) 38
24.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 122
78.7%
Uppercase Letter 21
 
13.5%
Space Separator 7
 
4.5%
Other Punctuation 5
 
3.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 32
26.2%
n 18
14.8%
d 15
12.3%
r 10
 
8.2%
t 8
 
6.6%
a 8
 
6.6%
c 7
 
5.7%
u 6
 
4.9%
i 6
 
4.9%
o 5
 
4.1%
Other values (4) 7
 
5.7%
Uppercase Letter
ValueCountFrequency (%)
S 5
23.8%
G 3
14.3%
Z 3
14.3%
E 2
 
9.5%
O 2
 
9.5%
A 2
 
9.5%
L 2
 
9.5%
U 2
 
9.5%
Other Punctuation
ValueCountFrequency (%)
. 4
80.0%
: 1
 
20.0%
Space Separator
ValueCountFrequency (%)
7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 143
92.3%
Common 12
 
7.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 32
22.4%
n 18
12.6%
d 15
10.5%
r 10
 
7.0%
t 8
 
5.6%
a 8
 
5.6%
c 7
 
4.9%
u 6
 
4.2%
i 6
 
4.2%
S 5
 
3.5%
Other values (12) 28
19.6%
Common
ValueCountFrequency (%)
7
58.3%
. 4
33.3%
: 1
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 155
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 32
20.6%
n 18
11.6%
d 15
 
9.7%
r 10
 
6.5%
t 8
 
5.2%
a 8
 
5.2%
c 7
 
4.5%
7
 
4.5%
u 6
 
3.9%
i 6
 
3.9%
Other values (15) 38
24.5%

method8
Text

MISSING 

Distinct3
Distinct (%)42.9%
Missing433
Missing (%)98.4%
Memory size14.1 KiB
2023-12-09T22:08:13.696258image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length15
Median length15
Mean length13
Min length8

Characters and Unicode

Total characters91
Distinct characters17
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)28.6%

Sample

1st rowZoned Guarantee
2nd rowZoned Guarantee
3rd rowZoned Guarantee
4th rowScreened
5th rowZoned Guarantee
ValueCountFrequency (%)
zoned 5
38.5%
guarantee 5
38.5%
screened 1
 
7.7%
ed 1
 
7.7%
opt 1
 
7.7%
2023-12-09T22:08:13.998773image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 18
19.8%
n 11
12.1%
a 10
11.0%
d 7
 
7.7%
6
 
6.6%
t 6
 
6.6%
r 6
 
6.6%
o 5
 
5.5%
Z 5
 
5.5%
u 5
 
5.5%
Other values (7) 12
13.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 70
76.9%
Uppercase Letter 13
 
14.3%
Space Separator 6
 
6.6%
Other Punctuation 2
 
2.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 18
25.7%
n 11
15.7%
a 10
14.3%
d 7
 
10.0%
t 6
 
8.6%
r 6
 
8.6%
o 5
 
7.1%
u 5
 
7.1%
c 1
 
1.4%
p 1
 
1.4%
Uppercase Letter
ValueCountFrequency (%)
Z 5
38.5%
G 5
38.5%
S 1
 
7.7%
E 1
 
7.7%
O 1
 
7.7%
Space Separator
ValueCountFrequency (%)
6
100.0%
Other Punctuation
ValueCountFrequency (%)
. 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 83
91.2%
Common 8
 
8.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 18
21.7%
n 11
13.3%
a 10
12.0%
d 7
 
8.4%
t 6
 
7.2%
r 6
 
7.2%
o 5
 
6.0%
Z 5
 
6.0%
u 5
 
6.0%
G 5
 
6.0%
Other values (5) 5
 
6.0%
Common
ValueCountFrequency (%)
6
75.0%
. 2
 
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 91
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 18
19.8%
n 11
12.1%
a 10
11.0%
d 7
 
7.7%
6
 
6.6%
t 6
 
6.6%
r 6
 
6.6%
o 5
 
5.5%
Z 5
 
5.5%
u 5
 
5.5%
Other values (7) 12
13.2%

method9
Text

MISSING 

Distinct2
Distinct (%)100.0%
Missing438
Missing (%)99.5%
Memory size13.9 KiB
2023-12-09T22:08:14.175158image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length15
Median length12.5
Mean length12.5
Min length10

Characters and Unicode

Total characters25
Distinct characters14
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st rowUnscreened
2nd rowZoned Guarantee
ValueCountFrequency (%)
zoned 1
33.3%
guarantee 1
33.3%
unscreened 1
33.3%
2023-12-09T22:08:14.472733image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 6
24.0%
n 4
16.0%
d 2
 
8.0%
a 2
 
8.0%
r 2
 
8.0%
Z 1
 
4.0%
o 1
 
4.0%
1
 
4.0%
G 1
 
4.0%
u 1
 
4.0%
Other values (4) 4
16.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 21
84.0%
Uppercase Letter 3
 
12.0%
Space Separator 1
 
4.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 6
28.6%
n 4
19.0%
d 2
 
9.5%
a 2
 
9.5%
r 2
 
9.5%
o 1
 
4.8%
u 1
 
4.8%
t 1
 
4.8%
s 1
 
4.8%
c 1
 
4.8%
Uppercase Letter
ValueCountFrequency (%)
Z 1
33.3%
G 1
33.3%
U 1
33.3%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 24
96.0%
Common 1
 
4.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 6
25.0%
n 4
16.7%
d 2
 
8.3%
a 2
 
8.3%
r 2
 
8.3%
Z 1
 
4.2%
o 1
 
4.2%
G 1
 
4.2%
u 1
 
4.2%
t 1
 
4.2%
Other values (3) 3
12.5%
Common
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 25
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 6
24.0%
n 4
16.0%
d 2
 
8.0%
a 2
 
8.0%
r 2
 
8.0%
Z 1
 
4.0%
o 1
 
4.0%
1
 
4.0%
G 1
 
4.0%
u 1
 
4.0%
Other values (4) 4
16.0%

method10
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing439
Missing (%)99.8%
Memory size13.9 KiB
2023-12-09T22:08:14.641978image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length15
Median length15
Mean length15
Min length15

Characters and Unicode

Total characters15
Distinct characters11
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowZoned Guarantee
ValueCountFrequency (%)
zoned 1
50.0%
guarantee 1
50.0%
2023-12-09T22:08:14.939552image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 3
20.0%
n 2
13.3%
a 2
13.3%
Z 1
 
6.7%
o 1
 
6.7%
d 1
 
6.7%
1
 
6.7%
G 1
 
6.7%
u 1
 
6.7%
r 1
 
6.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 12
80.0%
Uppercase Letter 2
 
13.3%
Space Separator 1
 
6.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 3
25.0%
n 2
16.7%
a 2
16.7%
o 1
 
8.3%
d 1
 
8.3%
u 1
 
8.3%
r 1
 
8.3%
t 1
 
8.3%
Uppercase Letter
ValueCountFrequency (%)
Z 1
50.0%
G 1
50.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 14
93.3%
Common 1
 
6.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 3
21.4%
n 2
14.3%
a 2
14.3%
Z 1
 
7.1%
o 1
 
7.1%
d 1
 
7.1%
G 1
 
7.1%
u 1
 
7.1%
r 1
 
7.1%
t 1
 
7.1%
Common
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 15
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 3
20.0%
n 2
13.3%
a 2
13.3%
Z 1
 
6.7%
o 1
 
6.7%
d 1
 
6.7%
1
 
6.7%
G 1
 
6.7%
u 1
 
6.7%
r 1
 
6.7%

seats9ge1
Text

MISSING 

Distinct106
Distinct (%)25.2%
Missing20
Missing (%)4.5%
Memory size25.0 KiB
2023-12-09T22:08:15.298871image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.207142857
Min length2

Characters and Unicode

Total characters927
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique53 ?
Unique (%)12.6%

Sample

1st row80
2nd row86
3rd row90
4th row69
5th row69
ValueCountFrequency (%)
90 54
 
12.9%
86 43
 
10.2%
68 37
 
8.8%
65 28
 
6.7%
92 20
 
4.8%
69 12
 
2.9%
125 8
 
1.9%
83 8
 
1.9%
50 8
 
1.9%
76 7
 
1.7%
Other values (96) 195
46.4%
2023-12-09T22:08:15.782236image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6 157
16.9%
8 124
13.4%
9 119
12.8%
0 113
12.2%
5 95
10.2%
1 93
10.0%
2 79
8.5%
3 50
 
5.4%
4 49
 
5.3%
7 48
 
5.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 927
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
6 157
16.9%
8 124
13.4%
9 119
12.8%
0 113
12.2%
5 95
10.2%
1 93
10.0%
2 79
8.5%
3 50
 
5.4%
4 49
 
5.3%
7 48
 
5.2%

Most occurring scripts

ValueCountFrequency (%)
Common 927
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
6 157
16.9%
8 124
13.4%
9 119
12.8%
0 113
12.2%
5 95
10.2%
1 93
10.0%
2 79
8.5%
3 50
 
5.4%
4 49
 
5.3%
7 48
 
5.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 927
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6 157
16.9%
8 124
13.4%
9 119
12.8%
0 113
12.2%
5 95
10.2%
1 93
10.0%
2 79
8.5%
3 50
 
5.4%
4 49
 
5.3%
7 48
 
5.2%

seats9ge2
Text

MISSING 

Distinct59
Distinct (%)52.7%
Missing328
Missing (%)74.5%
Memory size16.8 KiB
2023-12-09T22:08:16.074209image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.133928571
Min length2

Characters and Unicode

Total characters239
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique31 ?
Unique (%)27.7%

Sample

1st row68
2nd row23
3rd row41
4th row43
5th row23
ValueCountFrequency (%)
23 6
 
5.4%
43 6
 
5.4%
45 6
 
5.4%
25 5
 
4.5%
42 4
 
3.6%
57 4
 
3.6%
67 4
 
3.6%
86 3
 
2.7%
46 3
 
2.7%
50 3
 
2.7%
Other values (49) 68
60.7%
2023-12-09T22:08:16.510189image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 35
14.6%
2 33
13.8%
3 32
13.4%
5 31
13.0%
1 25
10.5%
6 20
8.4%
0 18
7.5%
7 17
7.1%
8 16
6.7%
9 12
 
5.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 239
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 35
14.6%
2 33
13.8%
3 32
13.4%
5 31
13.0%
1 25
10.5%
6 20
8.4%
0 18
7.5%
7 17
7.1%
8 16
6.7%
9 12
 
5.0%

Most occurring scripts

ValueCountFrequency (%)
Common 239
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
4 35
14.6%
2 33
13.8%
3 32
13.4%
5 31
13.0%
1 25
10.5%
6 20
8.4%
0 18
7.5%
7 17
7.1%
8 16
6.7%
9 12
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 239
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 35
14.6%
2 33
13.8%
3 32
13.4%
5 31
13.0%
1 25
10.5%
6 20
8.4%
0 18
7.5%
7 17
7.1%
8 16
6.7%
9 12
 
5.0%

seats9ge3
Text

MISSING 

Distinct39
Distinct (%)61.9%
Missing377
Missing (%)85.7%
Memory size15.5 KiB
2023-12-09T22:08:16.752843image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.126984127
Min length2

Characters and Unicode

Total characters134
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique27 ?
Unique (%)42.9%

Sample

1st row29
2nd row23
3rd row19
4th row104
5th row28
ValueCountFrequency (%)
42 5
 
7.9%
28 4
 
6.3%
50 4
 
6.3%
27 4
 
6.3%
21 4
 
6.3%
23 3
 
4.8%
17 2
 
3.2%
55 2
 
3.2%
22 2
 
3.2%
85 2
 
3.2%
Other values (29) 31
49.2%
2023-12-09T22:08:17.114834image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 35
26.1%
1 19
14.2%
5 19
14.2%
7 14
 
10.4%
8 13
 
9.7%
4 10
 
7.5%
0 7
 
5.2%
3 7
 
5.2%
6 7
 
5.2%
9 3
 
2.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 134
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 35
26.1%
1 19
14.2%
5 19
14.2%
7 14
 
10.4%
8 13
 
9.7%
4 10
 
7.5%
0 7
 
5.2%
3 7
 
5.2%
6 7
 
5.2%
9 3
 
2.2%

Most occurring scripts

ValueCountFrequency (%)
Common 134
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 35
26.1%
1 19
14.2%
5 19
14.2%
7 14
 
10.4%
8 13
 
9.7%
4 10
 
7.5%
0 7
 
5.2%
3 7
 
5.2%
6 7
 
5.2%
9 3
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 134
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 35
26.1%
1 19
14.2%
5 19
14.2%
7 14
 
10.4%
8 13
 
9.7%
4 10
 
7.5%
0 7
 
5.2%
3 7
 
5.2%
6 7
 
5.2%
9 3
 
2.2%

seats9ge4
Text

MISSING 

Distinct31
Distinct (%)67.4%
Missing394
Missing (%)89.5%
Memory size15.1 KiB
2023-12-09T22:08:17.347195image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.02173913
Min length1

Characters and Unicode

Total characters93
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique23 ?
Unique (%)50.0%

Sample

1st row25
2nd row38
3rd row19
4th row77
5th row28
ValueCountFrequency (%)
25 5
 
10.9%
42 4
 
8.7%
55 3
 
6.5%
28 3
 
6.5%
47 2
 
4.3%
33 2
 
4.3%
86 2
 
4.3%
21 2
 
4.3%
19 1
 
2.2%
27 1
 
2.2%
Other values (21) 21
45.7%
2023-12-09T22:08:17.703080image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 22
23.7%
5 17
18.3%
8 11
11.8%
7 9
9.7%
3 9
9.7%
4 8
 
8.6%
1 7
 
7.5%
6 6
 
6.5%
9 2
 
2.2%
0 2
 
2.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 93
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 22
23.7%
5 17
18.3%
8 11
11.8%
7 9
9.7%
3 9
9.7%
4 8
 
8.6%
1 7
 
7.5%
6 6
 
6.5%
9 2
 
2.2%
0 2
 
2.2%

Most occurring scripts

ValueCountFrequency (%)
Common 93
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 22
23.7%
5 17
18.3%
8 11
11.8%
7 9
9.7%
3 9
9.7%
4 8
 
8.6%
1 7
 
7.5%
6 6
 
6.5%
9 2
 
2.2%
0 2
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 93
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 22
23.7%
5 17
18.3%
8 11
11.8%
7 9
9.7%
3 9
9.7%
4 8
 
8.6%
1 7
 
7.5%
6 6
 
6.5%
9 2
 
2.2%
0 2
 
2.2%

seats9ge5
Text

MISSING 

Distinct22
Distinct (%)71.0%
Missing409
Missing (%)93.0%
Memory size14.7 KiB
2023-12-09T22:08:17.918527image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.032258065
Min length2

Characters and Unicode

Total characters63
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique16 ?
Unique (%)51.6%

Sample

1st row23
2nd row48
3rd row28
4th row58
5th row58
ValueCountFrequency (%)
27 3
 
9.7%
58 3
 
9.7%
28 3
 
9.7%
47 2
 
6.5%
25 2
 
6.5%
48 2
 
6.5%
86 1
 
3.2%
13 1
 
3.2%
38 1
 
3.2%
85 1
 
3.2%
Other values (12) 12
38.7%
2023-12-09T22:08:18.257295image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 13
20.6%
8 11
17.5%
5 10
15.9%
7 7
11.1%
4 7
11.1%
3 5
 
7.9%
6 3
 
4.8%
0 3
 
4.8%
9 2
 
3.2%
1 2
 
3.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 63
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 13
20.6%
8 11
17.5%
5 10
15.9%
7 7
11.1%
4 7
11.1%
3 5
 
7.9%
6 3
 
4.8%
0 3
 
4.8%
9 2
 
3.2%
1 2
 
3.2%

Most occurring scripts

ValueCountFrequency (%)
Common 63
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 13
20.6%
8 11
17.5%
5 10
15.9%
7 7
11.1%
4 7
11.1%
3 5
 
7.9%
6 3
 
4.8%
0 3
 
4.8%
9 2
 
3.2%
1 2
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 63
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 13
20.6%
8 11
17.5%
5 10
15.9%
7 7
11.1%
4 7
11.1%
3 5
 
7.9%
6 3
 
4.8%
0 3
 
4.8%
9 2
 
3.2%
1 2
 
3.2%

seats9ge6
Text

MISSING 

Distinct16
Distinct (%)88.9%
Missing422
Missing (%)95.9%
Memory size14.4 KiB
2023-12-09T22:08:18.440395image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.055555556
Min length2

Characters and Unicode

Total characters37
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique15 ?
Unique (%)83.3%

Sample

1st row23
2nd row60
3rd row28
4th row58
5th row38
ValueCountFrequency (%)
55 3
16.7%
58 1
 
5.6%
25 1
 
5.6%
42 1
 
5.6%
48 1
 
5.6%
12 1
 
5.6%
23 1
 
5.6%
57 1
 
5.6%
28 1
 
5.6%
63 1
 
5.6%
Other values (6) 6
33.3%
2023-12-09T22:08:18.754831image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 9
24.3%
2 7
18.9%
3 5
13.5%
8 4
10.8%
4 3
 
8.1%
1 2
 
5.4%
7 2
 
5.4%
6 2
 
5.4%
0 2
 
5.4%
9 1
 
2.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 37
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 9
24.3%
2 7
18.9%
3 5
13.5%
8 4
10.8%
4 3
 
8.1%
1 2
 
5.4%
7 2
 
5.4%
6 2
 
5.4%
0 2
 
5.4%
9 1
 
2.7%

Most occurring scripts

ValueCountFrequency (%)
Common 37
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 9
24.3%
2 7
18.9%
3 5
13.5%
8 4
10.8%
4 3
 
8.1%
1 2
 
5.4%
7 2
 
5.4%
6 2
 
5.4%
0 2
 
5.4%
9 1
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 37
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 9
24.3%
2 7
18.9%
3 5
13.5%
8 4
10.8%
4 3
 
8.1%
1 2
 
5.4%
7 2
 
5.4%
6 2
 
5.4%
0 2
 
5.4%
9 1
 
2.7%

seats9ge7
Text

MISSING 

Distinct8
Distinct (%)72.7%
Missing429
Missing (%)97.5%
Memory size14.2 KiB
2023-12-09T22:08:18.960188image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters22
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)45.5%

Sample

1st row58
2nd row22
3rd row25
4th row58
5th row27
ValueCountFrequency (%)
27 2
18.2%
58 2
18.2%
22 2
18.2%
55 1
9.1%
72 1
9.1%
42 1
9.1%
75 1
9.1%
25 1
9.1%
2023-12-09T22:08:19.274967image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 9
40.9%
5 6
27.3%
7 4
18.2%
8 2
 
9.1%
4 1
 
4.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 22
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 9
40.9%
5 6
27.3%
7 4
18.2%
8 2
 
9.1%
4 1
 
4.5%

Most occurring scripts

ValueCountFrequency (%)
Common 22
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 9
40.9%
5 6
27.3%
7 4
18.2%
8 2
 
9.1%
4 1
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 22
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 9
40.9%
5 6
27.3%
7 4
18.2%
8 2
 
9.1%
4 1
 
4.5%

seats9ge8
Text

MISSING 

Distinct2
Distinct (%)100.0%
Missing438
Missing (%)99.5%
Memory size13.9 KiB
2023-12-09T22:08:19.431826image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters4
Distinct characters3
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st row68
2nd row55
ValueCountFrequency (%)
68 1
50.0%
55 1
50.0%
2023-12-09T22:08:19.708619image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 2
50.0%
6 1
25.0%
8 1
25.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 2
50.0%
6 1
25.0%
8 1
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 2
50.0%
6 1
25.0%
8 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 2
50.0%
6 1
25.0%
8 1
25.0%

seats9ge9
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing439
Missing (%)99.8%
Memory size13.9 KiB
2023-12-09T22:08:19.835705image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters2
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row55
ValueCountFrequency (%)
55 1
100.0%
2023-12-09T22:08:20.082362image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 2
100.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 2
100.0%

seats9ge10
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing440
Missing (%)100.0%
Memory size3.6 KiB

grade9gefilledflag1
Text

MISSING 

Distinct2
Distinct (%)0.5%
Missing23
Missing (%)5.2%
Memory size24.5 KiB
2023-12-09T22:08:20.208235image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters417
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowY
2nd rowN
3rd rowN
4th rowN
5th rowY
ValueCountFrequency (%)
y 213
51.1%
n 204
48.9%
2023-12-09T22:08:20.443089image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
Y 213
51.1%
N 204
48.9%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 417
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
Y 213
51.1%
N 204
48.9%

Most occurring scripts

ValueCountFrequency (%)
Latin 417
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
Y 213
51.1%
N 204
48.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 417
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
Y 213
51.1%
N 204
48.9%

grade9gefilledflag2
Text

MISSING 

Distinct2
Distinct (%)1.8%
Missing328
Missing (%)74.5%
Memory size16.7 KiB
2023-12-09T22:08:20.570088image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters112
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowN
2nd rowY
3rd rowY
4th rowY
5th rowY
ValueCountFrequency (%)
y 56
50.0%
n 56
50.0%
2023-12-09T22:08:20.809821image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
Y 56
50.0%
N 56
50.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 112
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
Y 56
50.0%
N 56
50.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 112
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
Y 56
50.0%
N 56
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 112
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
Y 56
50.0%
N 56
50.0%

grade9gefilledflag3
Text

MISSING 

Distinct2
Distinct (%)3.2%
Missing377
Missing (%)85.7%
Memory size15.5 KiB
2023-12-09T22:08:20.929624image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters63
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowY
2nd rowY
3rd rowY
4th rowN
5th rowN
ValueCountFrequency (%)
n 36
57.1%
y 27
42.9%
2023-12-09T22:08:21.183850image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 36
57.1%
Y 27
42.9%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 63
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N 36
57.1%
Y 27
42.9%

Most occurring scripts

ValueCountFrequency (%)
Latin 63
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 36
57.1%
Y 27
42.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 63
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 36
57.1%
Y 27
42.9%

grade9gefilledflag4
Text

MISSING 

Distinct2
Distinct (%)4.3%
Missing394
Missing (%)89.5%
Memory size15.0 KiB
2023-12-09T22:08:21.296506image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters46
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowY
2nd rowY
3rd rowN
4th rowN
5th rowN
ValueCountFrequency (%)
n 26
56.5%
y 20
43.5%
2023-12-09T22:08:21.530480image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 26
56.5%
Y 20
43.5%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 46
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N 26
56.5%
Y 20
43.5%

Most occurring scripts

ValueCountFrequency (%)
Latin 46
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 26
56.5%
Y 20
43.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 46
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 26
56.5%
Y 20
43.5%

grade9gefilledflag5
Text

MISSING 

Distinct2
Distinct (%)6.5%
Missing409
Missing (%)93.0%
Memory size14.7 KiB
2023-12-09T22:08:21.645008image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters31
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowY
2nd rowN
3rd rowN
4th rowN
5th rowY
ValueCountFrequency (%)
n 17
54.8%
y 14
45.2%
2023-12-09T22:08:21.869019image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 17
54.8%
Y 14
45.2%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 31
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N 17
54.8%
Y 14
45.2%

Most occurring scripts

ValueCountFrequency (%)
Latin 31
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 17
54.8%
Y 14
45.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 31
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 17
54.8%
Y 14
45.2%

grade9gefilledflag6
Text

MISSING 

Distinct2
Distinct (%)11.1%
Missing422
Missing (%)95.9%
Memory size14.3 KiB
2023-12-09T22:08:21.980886image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters18
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowY
2nd rowN
3rd rowY
4th rowY
5th rowN
ValueCountFrequency (%)
y 12
66.7%
n 6
33.3%
2023-12-09T22:08:22.227852image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
Y 12
66.7%
N 6
33.3%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 18
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
Y 12
66.7%
N 6
33.3%

Most occurring scripts

ValueCountFrequency (%)
Latin 18
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
Y 12
66.7%
N 6
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 18
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
Y 12
66.7%
N 6
33.3%

grade9gefilledflag7
Text

MISSING 

Distinct2
Distinct (%)18.2%
Missing429
Missing (%)97.5%
Memory size14.2 KiB
2023-12-09T22:08:22.350270image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters11
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowY
2nd rowN
3rd rowN
4th rowN
5th rowY
ValueCountFrequency (%)
n 6
54.5%
y 5
45.5%
2023-12-09T22:08:22.600863image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 6
54.5%
Y 5
45.5%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 11
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N 6
54.5%
Y 5
45.5%

Most occurring scripts

ValueCountFrequency (%)
Latin 11
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 6
54.5%
Y 5
45.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 6
54.5%
Y 5
45.5%

grade9gefilledflag8
Text

MISSING 

Distinct2
Distinct (%)100.0%
Missing438
Missing (%)99.5%
Memory size13.9 KiB
2023-12-09T22:08:22.713977image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters2
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st rowN
2nd rowY
ValueCountFrequency (%)
y 1
50.0%
n 1
50.0%
2023-12-09T22:08:22.933896image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
Y 1
50.0%
N 1
50.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 2
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
Y 1
50.0%
N 1
50.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
Y 1
50.0%
N 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
Y 1
50.0%
N 1
50.0%

grade9gefilledflag9
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing439
Missing (%)99.8%
Memory size13.9 KiB
2023-12-09T22:08:23.039315image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowN
ValueCountFrequency (%)
n 1
100.0%
2023-12-09T22:08:23.267154image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 1
100.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 1
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 1
100.0%

grade9gefilledflag10
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing440
Missing (%)100.0%
Memory size3.6 KiB

grade9geapplicants1
Text

MISSING 

Distinct354
Distinct (%)84.3%
Missing20
Missing (%)4.5%
Memory size25.4 KiB
2023-12-09T22:08:23.769675image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length4
Median length3
Mean length3.2
Min length2

Characters and Unicode

Total characters1344
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique298 ?
Unique (%)71.0%

Sample

1st row1515
2nd row330
3rd row265
4th row194
5th row334
ValueCountFrequency (%)
391 3
 
0.7%
610 3
 
0.7%
194 3
 
0.7%
212 3
 
0.7%
158 3
 
0.7%
314 3
 
0.7%
234 3
 
0.7%
311 3
 
0.7%
239 3
 
0.7%
143 3
 
0.7%
Other values (344) 390
92.9%
2023-12-09T22:08:24.433239image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 226
16.8%
3 181
13.5%
2 170
12.6%
4 153
11.4%
5 110
8.2%
0 109
8.1%
6 106
7.9%
9 105
7.8%
8 96
7.1%
7 88
 
6.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1344
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 226
16.8%
3 181
13.5%
2 170
12.6%
4 153
11.4%
5 110
8.2%
0 109
8.1%
6 106
7.9%
9 105
7.8%
8 96
7.1%
7 88
 
6.5%

Most occurring scripts

ValueCountFrequency (%)
Common 1344
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 226
16.8%
3 181
13.5%
2 170
12.6%
4 153
11.4%
5 110
8.2%
0 109
8.1%
6 106
7.9%
9 105
7.8%
8 96
7.1%
7 88
 
6.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1344
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 226
16.8%
3 181
13.5%
2 170
12.6%
4 153
11.4%
5 110
8.2%
0 109
8.1%
6 106
7.9%
9 105
7.8%
8 96
7.1%
7 88
 
6.5%

grade9geapplicants2
Text

MISSING 

Distinct101
Distinct (%)90.2%
Missing328
Missing (%)74.5%
Memory size16.9 KiB
2023-12-09T22:08:24.815805image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length4
Median length3
Mean length2.919642857
Min length2

Characters and Unicode

Total characters327
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique90 ?
Unique (%)80.4%

Sample

1st row284
2nd row262
3rd row538
4th row318
5th row321
ValueCountFrequency (%)
54 2
 
1.8%
143 2
 
1.8%
207 2
 
1.8%
120 2
 
1.8%
319 2
 
1.8%
136 2
 
1.8%
25 2
 
1.8%
235 2
 
1.8%
363 2
 
1.8%
94 2
 
1.8%
Other values (91) 92
82.1%
2023-12-09T22:08:25.340832image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 55
16.8%
2 49
15.0%
3 38
11.6%
5 34
10.4%
4 29
8.9%
0 28
8.6%
7 27
8.3%
6 26
8.0%
9 21
 
6.4%
8 20
 
6.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 327
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 55
16.8%
2 49
15.0%
3 38
11.6%
5 34
10.4%
4 29
8.9%
0 28
8.6%
7 27
8.3%
6 26
8.0%
9 21
 
6.4%
8 20
 
6.1%

Most occurring scripts

ValueCountFrequency (%)
Common 327
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 55
16.8%
2 49
15.0%
3 38
11.6%
5 34
10.4%
4 29
8.9%
0 28
8.6%
7 27
8.3%
6 26
8.0%
9 21
 
6.4%
8 20
 
6.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 327
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 55
16.8%
2 49
15.0%
3 38
11.6%
5 34
10.4%
4 29
8.9%
0 28
8.6%
7 27
8.3%
6 26
8.0%
9 21
 
6.4%
8 20
 
6.1%

grade9geapplicants3
Text

MISSING 

Distinct62
Distinct (%)98.4%
Missing377
Missing (%)85.7%
Memory size15.6 KiB
2023-12-09T22:08:25.632257image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length4
Median length3
Mean length2.952380952
Min length2

Characters and Unicode

Total characters186
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique61 ?
Unique (%)96.8%

Sample

1st row335
2nd row181
3rd row148
4th row432
5th row84
ValueCountFrequency (%)
84 2
 
3.2%
155 1
 
1.6%
199 1
 
1.6%
62 1
 
1.6%
181 1
 
1.6%
409 1
 
1.6%
955 1
 
1.6%
711 1
 
1.6%
1950 1
 
1.6%
150 1
 
1.6%
Other values (52) 52
82.5%
2023-12-09T22:08:26.058365image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 38
20.4%
3 21
11.3%
5 21
11.3%
4 19
10.2%
8 18
9.7%
9 16
8.6%
2 15
 
8.1%
0 14
 
7.5%
6 14
 
7.5%
7 10
 
5.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 186
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 38
20.4%
3 21
11.3%
5 21
11.3%
4 19
10.2%
8 18
9.7%
9 16
8.6%
2 15
 
8.1%
0 14
 
7.5%
6 14
 
7.5%
7 10
 
5.4%

Most occurring scripts

ValueCountFrequency (%)
Common 186
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 38
20.4%
3 21
11.3%
5 21
11.3%
4 19
10.2%
8 18
9.7%
9 16
8.6%
2 15
 
8.1%
0 14
 
7.5%
6 14
 
7.5%
7 10
 
5.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 186
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 38
20.4%
3 21
11.3%
5 21
11.3%
4 19
10.2%
8 18
9.7%
9 16
8.6%
2 15
 
8.1%
0 14
 
7.5%
6 14
 
7.5%
7 10
 
5.4%

grade9geapplicants4
Text

MISSING 

Distinct43
Distinct (%)93.5%
Missing394
Missing (%)89.5%
Memory size15.1 KiB
2023-12-09T22:08:26.332179image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length4
Median length3
Mean length2.847826087
Min length2

Characters and Unicode

Total characters131
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique40 ?
Unique (%)87.0%

Sample

1st row550
2nd row363
3rd row82
4th row158
5th row43
ValueCountFrequency (%)
213 2
 
4.3%
198 2
 
4.3%
120 2
 
4.3%
515 1
 
2.2%
80 1
 
2.2%
219 1
 
2.2%
184 1
 
2.2%
43 1
 
2.2%
60 1
 
2.2%
100 1
 
2.2%
Other values (33) 33
71.7%
2023-12-09T22:08:26.786806image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 27
20.6%
2 17
13.0%
8 16
12.2%
3 15
11.5%
6 12
9.2%
0 11
8.4%
9 9
 
6.9%
5 9
 
6.9%
4 8
 
6.1%
7 7
 
5.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 131
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 27
20.6%
2 17
13.0%
8 16
12.2%
3 15
11.5%
6 12
9.2%
0 11
8.4%
9 9
 
6.9%
5 9
 
6.9%
4 8
 
6.1%
7 7
 
5.3%

Most occurring scripts

ValueCountFrequency (%)
Common 131
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 27
20.6%
2 17
13.0%
8 16
12.2%
3 15
11.5%
6 12
9.2%
0 11
8.4%
9 9
 
6.9%
5 9
 
6.9%
4 8
 
6.1%
7 7
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 131
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 27
20.6%
2 17
13.0%
8 16
12.2%
3 15
11.5%
6 12
9.2%
0 11
8.4%
9 9
 
6.9%
5 9
 
6.9%
4 8
 
6.1%
7 7
 
5.3%

grade9geapplicants5
Text

MISSING 

Distinct31
Distinct (%)100.0%
Missing409
Missing (%)93.0%
Memory size14.7 KiB
2023-12-09T22:08:27.058769image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length4
Median length3
Mean length2.838709677
Min length2

Characters and Unicode

Total characters88
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique31 ?
Unique (%)100.0%

Sample

1st row468
2nd row173
3rd row77
4th row137
5th row328
ValueCountFrequency (%)
168 1
 
3.2%
1233 1
 
3.2%
187 1
 
3.2%
105 1
 
3.2%
328 1
 
3.2%
719 1
 
3.2%
137 1
 
3.2%
173 1
 
3.2%
249 1
 
3.2%
104 1
 
3.2%
Other values (21) 21
67.7%
2023-12-09T22:08:27.447916image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 18
20.5%
3 12
13.6%
4 10
11.4%
2 10
11.4%
8 9
10.2%
7 8
9.1%
6 7
 
8.0%
5 6
 
6.8%
9 5
 
5.7%
0 3
 
3.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 88
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 18
20.5%
3 12
13.6%
4 10
11.4%
2 10
11.4%
8 9
10.2%
7 8
9.1%
6 7
 
8.0%
5 6
 
6.8%
9 5
 
5.7%
0 3
 
3.4%

Most occurring scripts

ValueCountFrequency (%)
Common 88
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 18
20.5%
3 12
13.6%
4 10
11.4%
2 10
11.4%
8 9
10.2%
7 8
9.1%
6 7
 
8.0%
5 6
 
6.8%
9 5
 
5.7%
0 3
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 88
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 18
20.5%
3 12
13.6%
4 10
11.4%
2 10
11.4%
8 9
10.2%
7 8
9.1%
6 7
 
8.0%
5 6
 
6.8%
9 5
 
5.7%
0 3
 
3.4%

grade9geapplicants6
Text

MISSING 

Distinct18
Distinct (%)100.0%
Missing422
Missing (%)95.9%
Memory size14.4 KiB
2023-12-09T22:08:27.677061image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length4
Median length3
Mean length3
Min length2

Characters and Unicode

Total characters54
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique18 ?
Unique (%)100.0%

Sample

1st row448
2nd row232
3rd row229
4th row677
5th row116
ValueCountFrequency (%)
232 1
 
5.6%
242 1
 
5.6%
677 1
 
5.6%
445 1
 
5.6%
351 1
 
5.6%
229 1
 
5.6%
258 1
 
5.6%
29 1
 
5.6%
116 1
 
5.6%
279 1
 
5.6%
Other values (8) 8
44.4%
2023-12-09T22:08:28.052569image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 10
18.5%
1 8
14.8%
3 6
11.1%
5 6
11.1%
4 5
9.3%
6 5
9.3%
7 5
9.3%
8 4
 
7.4%
9 4
 
7.4%
0 1
 
1.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 54
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 10
18.5%
1 8
14.8%
3 6
11.1%
5 6
11.1%
4 5
9.3%
6 5
9.3%
7 5
9.3%
8 4
 
7.4%
9 4
 
7.4%
0 1
 
1.9%

Most occurring scripts

ValueCountFrequency (%)
Common 54
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 10
18.5%
1 8
14.8%
3 6
11.1%
5 6
11.1%
4 5
9.3%
6 5
9.3%
7 5
9.3%
8 4
 
7.4%
9 4
 
7.4%
0 1
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 54
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 10
18.5%
1 8
14.8%
3 6
11.1%
5 6
11.1%
4 5
9.3%
6 5
9.3%
7 5
9.3%
8 4
 
7.4%
9 4
 
7.4%
0 1
 
1.9%

grade9geapplicants7
Text

MISSING 

Distinct11
Distinct (%)100.0%
Missing429
Missing (%)97.5%
Memory size14.2 KiB
2023-12-09T22:08:28.265411image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.909090909
Min length2

Characters and Unicode

Total characters32
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique11 ?
Unique (%)100.0%

Sample

1st row490
2nd row102
3rd row126
4th row41
5th row297
ValueCountFrequency (%)
243 1
9.1%
41 1
9.1%
297 1
9.1%
102 1
9.1%
490 1
9.1%
126 1
9.1%
590 1
9.1%
198 1
9.1%
149 1
9.1%
885 1
9.1%
2023-12-09T22:08:28.603857image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 7
21.9%
9 5
15.6%
2 4
12.5%
4 4
12.5%
0 3
9.4%
5 3
9.4%
8 3
9.4%
3 1
 
3.1%
7 1
 
3.1%
6 1
 
3.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 32
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 7
21.9%
9 5
15.6%
2 4
12.5%
4 4
12.5%
0 3
9.4%
5 3
9.4%
8 3
9.4%
3 1
 
3.1%
7 1
 
3.1%
6 1
 
3.1%

Most occurring scripts

ValueCountFrequency (%)
Common 32
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 7
21.9%
9 5
15.6%
2 4
12.5%
4 4
12.5%
0 3
9.4%
5 3
9.4%
8 3
9.4%
3 1
 
3.1%
7 1
 
3.1%
6 1
 
3.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 32
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 7
21.9%
9 5
15.6%
2 4
12.5%
4 4
12.5%
0 3
9.4%
5 3
9.4%
8 3
9.4%
3 1
 
3.1%
7 1
 
3.1%
6 1
 
3.1%

grade9geapplicants8
Text

MISSING 

Distinct2
Distinct (%)100.0%
Missing438
Missing (%)99.5%
Memory size13.9 KiB
2023-12-09T22:08:28.770617image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters6
Distinct characters6
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st row120
2nd row473
ValueCountFrequency (%)
473 1
50.0%
120 1
50.0%
2023-12-09T22:08:29.054432image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 1
16.7%
7 1
16.7%
3 1
16.7%
1 1
16.7%
2 1
16.7%
0 1
16.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 1
16.7%
7 1
16.7%
3 1
16.7%
1 1
16.7%
2 1
16.7%
0 1
16.7%

Most occurring scripts

ValueCountFrequency (%)
Common 6
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
4 1
16.7%
7 1
16.7%
3 1
16.7%
1 1
16.7%
2 1
16.7%
0 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 1
16.7%
7 1
16.7%
3 1
16.7%
1 1
16.7%
2 1
16.7%
0 1
16.7%

grade9geapplicants9
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing439
Missing (%)99.8%
Memory size13.9 KiB
2023-12-09T22:08:29.175851image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters3
Distinct characters3
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row176
ValueCountFrequency (%)
176 1
100.0%
2023-12-09T22:08:29.411627image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 1
33.3%
7 1
33.3%
6 1
33.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 1
33.3%
7 1
33.3%
6 1
33.3%

Most occurring scripts

ValueCountFrequency (%)
Common 3
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 1
33.3%
7 1
33.3%
6 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 1
33.3%
7 1
33.3%
6 1
33.3%

grade9geapplicants10
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing440
Missing (%)100.0%
Memory size3.6 KiB

seats9swd1
Text

MISSING 

Distinct45
Distinct (%)10.7%
Missing20
Missing (%)4.5%
Memory size24.9 KiB
2023-12-09T22:08:29.645198image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length1.907142857
Min length1

Characters and Unicode

Total characters801
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique12 ?
Unique (%)2.9%

Sample

1st row16
2nd row22
3rd row18
4th row12
5th row12
ValueCountFrequency (%)
18 60
14.3%
16 49
 
11.7%
13 47
 
11.2%
22 46
 
11.0%
15 16
 
3.8%
21 15
 
3.6%
12 14
 
3.3%
19 14
 
3.3%
25 13
 
3.1%
20 12
 
2.9%
Other values (35) 134
31.9%
2023-12-09T22:08:30.015362image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 268
33.5%
2 179
22.3%
3 70
 
8.7%
8 68
 
8.5%
6 60
 
7.5%
5 42
 
5.2%
9 31
 
3.9%
0 29
 
3.6%
4 28
 
3.5%
7 26
 
3.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 801
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 268
33.5%
2 179
22.3%
3 70
 
8.7%
8 68
 
8.5%
6 60
 
7.5%
5 42
 
5.2%
9 31
 
3.9%
0 29
 
3.6%
4 28
 
3.5%
7 26
 
3.2%

Most occurring scripts

ValueCountFrequency (%)
Common 801
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 268
33.5%
2 179
22.3%
3 70
 
8.7%
8 68
 
8.5%
6 60
 
7.5%
5 42
 
5.2%
9 31
 
3.9%
0 29
 
3.6%
4 28
 
3.5%
7 26
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 801
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 268
33.5%
2 179
22.3%
3 70
 
8.7%
8 68
 
8.5%
6 60
 
7.5%
5 42
 
5.2%
9 31
 
3.9%
0 29
 
3.6%
4 28
 
3.5%
7 26
 
3.2%

seats9swd2
Text

MISSING 

Distinct28
Distinct (%)24.8%
Missing327
Missing (%)74.3%
Memory size16.8 KiB
2023-12-09T22:08:30.221820image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length2
Mean length1.522123894
Min length1

Characters and Unicode

Total characters172
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8 ?
Unique (%)7.1%

Sample

1st row12
2nd row4
3rd row15
4th row11
5th row4
ValueCountFrequency (%)
5 12
 
10.6%
11 11
 
9.7%
4 10
 
8.8%
9 9
 
8.0%
12 8
 
7.1%
13 8
 
7.1%
7 7
 
6.2%
8 7
 
6.2%
6 5
 
4.4%
20 4
 
3.5%
Other values (18) 32
28.3%
2023-12-09T22:08:30.566352image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 55
32.0%
2 25
14.5%
5 17
 
9.9%
4 17
 
9.9%
3 11
 
6.4%
7 11
 
6.4%
6 10
 
5.8%
9 9
 
5.2%
0 9
 
5.2%
8 8
 
4.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 172
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 55
32.0%
2 25
14.5%
5 17
 
9.9%
4 17
 
9.9%
3 11
 
6.4%
7 11
 
6.4%
6 10
 
5.8%
9 9
 
5.2%
0 9
 
5.2%
8 8
 
4.7%

Most occurring scripts

ValueCountFrequency (%)
Common 172
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 55
32.0%
2 25
14.5%
5 17
 
9.9%
4 17
 
9.9%
3 11
 
6.4%
7 11
 
6.4%
6 10
 
5.8%
9 9
 
5.2%
0 9
 
5.2%
8 8
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 172
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 55
32.0%
2 25
14.5%
5 17
 
9.9%
4 17
 
9.9%
3 11
 
6.4%
7 11
 
6.4%
6 10
 
5.8%
9 9
 
5.2%
0 9
 
5.2%
8 8
 
4.7%

seats9swd3
Text

MISSING 

Distinct25
Distinct (%)39.7%
Missing377
Missing (%)85.7%
Memory size15.5 KiB
2023-12-09T22:08:30.769989image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.412698413
Min length1

Characters and Unicode

Total characters89
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique14 ?
Unique (%)22.2%

Sample

1st row3
2nd row4
3rd row5
4th row26
5th row6
ValueCountFrequency (%)
4 7
11.1%
6 7
11.1%
3 6
 
9.5%
8 5
 
7.9%
10 5
 
7.9%
13 4
 
6.3%
5 4
 
6.3%
7 4
 
6.3%
11 3
 
4.8%
25 2
 
3.2%
Other values (15) 16
25.4%
2023-12-09T22:08:31.108294image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 20
22.5%
3 12
13.5%
6 10
11.2%
2 10
11.2%
4 9
10.1%
0 8
 
9.0%
5 8
 
9.0%
7 6
 
6.7%
8 5
 
5.6%
9 1
 
1.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 89
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 20
22.5%
3 12
13.5%
6 10
11.2%
2 10
11.2%
4 9
10.1%
0 8
 
9.0%
5 8
 
9.0%
7 6
 
6.7%
8 5
 
5.6%
9 1
 
1.1%

Most occurring scripts

ValueCountFrequency (%)
Common 89
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 20
22.5%
3 12
13.5%
6 10
11.2%
2 10
11.2%
4 9
10.1%
0 8
 
9.0%
5 8
 
9.0%
7 6
 
6.7%
8 5
 
5.6%
9 1
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 89
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 20
22.5%
3 12
13.5%
6 10
11.2%
2 10
11.2%
4 9
10.1%
0 8
 
9.0%
5 8
 
9.0%
7 6
 
6.7%
8 5
 
5.6%
9 1
 
1.1%

seats9swd4
Text

MISSING 

Distinct18
Distinct (%)39.1%
Missing394
Missing (%)89.5%
Memory size15.1 KiB
2023-12-09T22:08:31.303516image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.347826087
Min length1

Characters and Unicode

Total characters62
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)10.9%

Sample

1st row7
2nd row7
3rd row5
4th row20
5th row6
ValueCountFrequency (%)
4 5
10.9%
7 5
10.9%
5 5
10.9%
6 5
10.9%
8 4
 
8.7%
13 3
 
6.5%
2 2
 
4.3%
20 2
 
4.3%
9 2
 
4.3%
10 2
 
4.3%
Other values (8) 11
23.9%
2023-12-09T22:08:31.621367image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 13
21.0%
5 7
11.3%
6 7
11.3%
4 6
9.7%
7 6
9.7%
8 6
9.7%
2 6
9.7%
0 5
 
8.1%
3 4
 
6.5%
9 2
 
3.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 62
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 13
21.0%
5 7
11.3%
6 7
11.3%
4 6
9.7%
7 6
9.7%
8 6
9.7%
2 6
9.7%
0 5
 
8.1%
3 4
 
6.5%
9 2
 
3.2%

Most occurring scripts

ValueCountFrequency (%)
Common 62
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 13
21.0%
5 7
11.3%
6 7
11.3%
4 6
9.7%
7 6
9.7%
8 6
9.7%
2 6
9.7%
0 5
 
8.1%
3 4
 
6.5%
9 2
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 62
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 13
21.0%
5 7
11.3%
6 7
11.3%
4 6
9.7%
7 6
9.7%
8 6
9.7%
2 6
9.7%
0 5
 
8.1%
3 4
 
6.5%
9 2
 
3.2%

seats9swd5
Text

MISSING 

Distinct16
Distinct (%)51.6%
Missing409
Missing (%)93.0%
Memory size14.7 KiB
2023-12-09T22:08:31.790375image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.451612903
Min length1

Characters and Unicode

Total characters45
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8 ?
Unique (%)25.8%

Sample

1st row2
2nd row12
3rd row6
4th row10
5th row10
ValueCountFrequency (%)
6 5
16.1%
7 4
12.9%
12 3
9.7%
10 3
9.7%
2 2
 
6.5%
9 2
 
6.5%
11 2
 
6.5%
5 2
 
6.5%
24 1
 
3.2%
8 1
 
3.2%
Other values (6) 6
19.4%
2023-12-09T22:08:32.102712image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 15
33.3%
2 7
15.6%
6 6
 
13.3%
7 4
 
8.9%
0 3
 
6.7%
5 3
 
6.7%
9 2
 
4.4%
4 2
 
4.4%
3 2
 
4.4%
8 1
 
2.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 45
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 15
33.3%
2 7
15.6%
6 6
 
13.3%
7 4
 
8.9%
0 3
 
6.7%
5 3
 
6.7%
9 2
 
4.4%
4 2
 
4.4%
3 2
 
4.4%
8 1
 
2.2%

Most occurring scripts

ValueCountFrequency (%)
Common 45
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 15
33.3%
2 7
15.6%
6 6
 
13.3%
7 4
 
8.9%
0 3
 
6.7%
5 3
 
6.7%
9 2
 
4.4%
4 2
 
4.4%
3 2
 
4.4%
8 1
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 45
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 15
33.3%
2 7
15.6%
6 6
 
13.3%
7 4
 
8.9%
0 3
 
6.7%
5 3
 
6.7%
9 2
 
4.4%
4 2
 
4.4%
3 2
 
4.4%
8 1
 
2.2%

seats9swd6
Text

MISSING 

Distinct13
Distinct (%)72.2%
Missing422
Missing (%)95.9%
Memory size14.3 KiB
2023-12-09T22:08:32.294751image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length2
Mean length1.555555556
Min length1

Characters and Unicode

Total characters28
Distinct characters9
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10 ?
Unique (%)55.6%

Sample

1st row2
2nd row15
3rd row6
4th row10
5th row10
ValueCountFrequency (%)
10 3
16.7%
13 3
16.7%
5 2
11.1%
2 1
 
5.6%
8 1
 
5.6%
21 1
 
5.6%
12 1
 
5.6%
15 1
 
5.6%
4 1
 
5.6%
3 1
 
5.6%
Other values (3) 3
16.7%
2023-12-09T22:08:32.602475image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 11
39.3%
3 4
 
14.3%
0 3
 
10.7%
5 3
 
10.7%
2 3
 
10.7%
8 1
 
3.6%
4 1
 
3.6%
7 1
 
3.6%
6 1
 
3.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 28
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 11
39.3%
3 4
 
14.3%
0 3
 
10.7%
5 3
 
10.7%
2 3
 
10.7%
8 1
 
3.6%
4 1
 
3.6%
7 1
 
3.6%
6 1
 
3.6%

Most occurring scripts

ValueCountFrequency (%)
Common 28
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 11
39.3%
3 4
 
14.3%
0 3
 
10.7%
5 3
 
10.7%
2 3
 
10.7%
8 1
 
3.6%
4 1
 
3.6%
7 1
 
3.6%
6 1
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 28
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 11
39.3%
3 4
 
14.3%
0 3
 
10.7%
5 3
 
10.7%
2 3
 
10.7%
8 1
 
3.6%
4 1
 
3.6%
7 1
 
3.6%
6 1
 
3.6%

seats9swd7
Text

MISSING 

Distinct8
Distinct (%)72.7%
Missing429
Missing (%)97.5%
Memory size14.2 KiB
2023-12-09T22:08:32.780625image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.454545455
Min length1

Characters and Unicode

Total characters16
Distinct characters8
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)45.5%

Sample

1st row10
2nd row6
3rd row5
4th row10
5th row5
ValueCountFrequency (%)
10 2
18.2%
5 2
18.2%
6 2
18.2%
13 1
9.1%
18 1
9.1%
2 1
9.1%
15 1
9.1%
7 1
9.1%
2023-12-09T22:08:33.086356image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 5
31.2%
5 3
18.8%
0 2
 
12.5%
6 2
 
12.5%
3 1
 
6.2%
8 1
 
6.2%
2 1
 
6.2%
7 1
 
6.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 16
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 5
31.2%
5 3
18.8%
0 2
 
12.5%
6 2
 
12.5%
3 1
 
6.2%
8 1
 
6.2%
2 1
 
6.2%
7 1
 
6.2%

Most occurring scripts

ValueCountFrequency (%)
Common 16
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 5
31.2%
5 3
18.8%
0 2
 
12.5%
6 2
 
12.5%
3 1
 
6.2%
8 1
 
6.2%
2 1
 
6.2%
7 1
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 16
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 5
31.2%
5 3
18.8%
0 2
 
12.5%
6 2
 
12.5%
3 1
 
6.2%
8 1
 
6.2%
2 1
 
6.2%
7 1
 
6.2%

seats9swd8
Text

MISSING 

Distinct2
Distinct (%)100.0%
Missing438
Missing (%)99.5%
Memory size13.9 KiB
2023-12-09T22:08:33.250023image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters4
Distinct characters3
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st row17
2nd row13
ValueCountFrequency (%)
13 1
50.0%
17 1
50.0%
2023-12-09T22:08:33.521095image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 2
50.0%
3 1
25.0%
7 1
25.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 2
50.0%
3 1
25.0%
7 1
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 2
50.0%
3 1
25.0%
7 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 2
50.0%
3 1
25.0%
7 1
25.0%

seats9swd9
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing439
Missing (%)99.8%
Memory size13.9 KiB
2023-12-09T22:08:33.625981image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters2
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row13
ValueCountFrequency (%)
13 1
100.0%
2023-12-09T22:08:33.845757image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 1
50.0%
3 1
50.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 1
50.0%
3 1
50.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 1
50.0%
3 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 1
50.0%
3 1
50.0%

seats9swd10
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing440
Missing (%)100.0%
Memory size3.6 KiB

grade9swdfilledflag1
Text

MISSING 

Distinct2
Distinct (%)0.5%
Missing23
Missing (%)5.2%
Memory size24.5 KiB
2023-12-09T22:08:33.956499image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters417
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowY
2nd rowN
3rd rowN
4th rowN
5th rowY
ValueCountFrequency (%)
n 212
50.8%
y 205
49.2%
2023-12-09T22:08:34.177498image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 212
50.8%
Y 205
49.2%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 417
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N 212
50.8%
Y 205
49.2%

Most occurring scripts

ValueCountFrequency (%)
Latin 417
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 212
50.8%
Y 205
49.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 417
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 212
50.8%
Y 205
49.2%

grade9swdfilledflag2
Text

MISSING 

Distinct2
Distinct (%)1.8%
Missing328
Missing (%)74.5%
Memory size16.7 KiB
2023-12-09T22:08:34.287749image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters112
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowN
2nd rowY
3rd rowN
4th rowY
5th rowN
ValueCountFrequency (%)
n 70
62.5%
y 42
37.5%
2023-12-09T22:08:34.518969image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 70
62.5%
Y 42
37.5%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 112
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N 70
62.5%
Y 42
37.5%

Most occurring scripts

ValueCountFrequency (%)
Latin 112
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 70
62.5%
Y 42
37.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 112
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 70
62.5%
Y 42
37.5%

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Text

MISSING 

Distinct2
Distinct (%)3.2%
Missing377
Missing (%)85.7%
Memory size15.5 KiB
2023-12-09T22:08:34.630862image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters63
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowN
2nd rowN
3rd rowY
4th rowY
5th rowN
ValueCountFrequency (%)
n 39
61.9%
y 24
38.1%
2023-12-09T22:08:34.864938image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 39
61.9%
Y 24
38.1%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 63
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N 39
61.9%
Y 24
38.1%

Most occurring scripts

ValueCountFrequency (%)
Latin 63
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 39
61.9%
Y 24
38.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 63
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 39
61.9%
Y 24
38.1%

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Text

MISSING 

Distinct2
Distinct (%)4.3%
Missing394
Missing (%)89.5%
Memory size15.0 KiB
2023-12-09T22:08:34.974740image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters46
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowN
2nd rowN
3rd rowN
4th rowN
5th rowN
ValueCountFrequency (%)
n 36
78.3%
y 10
 
21.7%
2023-12-09T22:08:35.194468image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 36
78.3%
Y 10
 
21.7%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 46
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N 36
78.3%
Y 10
 
21.7%

Most occurring scripts

ValueCountFrequency (%)
Latin 46
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 36
78.3%
Y 10
 
21.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 46
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 36
78.3%
Y 10
 
21.7%

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Text

MISSING 

Distinct2
Distinct (%)6.5%
Missing409
Missing (%)93.0%
Memory size14.7 KiB
2023-12-09T22:08:35.311035image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters31
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowY
2nd rowN
3rd rowN
4th rowN
5th rowY
ValueCountFrequency (%)
n 18
58.1%
y 13
41.9%
2023-12-09T22:08:35.549886image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 18
58.1%
Y 13
41.9%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 31
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N 18
58.1%
Y 13
41.9%

Most occurring scripts

ValueCountFrequency (%)
Latin 31
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 18
58.1%
Y 13
41.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 31
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 18
58.1%
Y 13
41.9%

grade9swdfilledflag6
Text

MISSING 

Distinct2
Distinct (%)11.1%
Missing422
Missing (%)95.9%
Memory size14.3 KiB
2023-12-09T22:08:35.663622image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters18
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowY
2nd rowN
3rd rowY
4th rowY
5th rowY
ValueCountFrequency (%)
y 13
72.2%
n 5
 
27.8%
2023-12-09T22:08:35.902105image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
Y 13
72.2%
N 5
 
27.8%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 18
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
Y 13
72.2%
N 5
 
27.8%

Most occurring scripts

ValueCountFrequency (%)
Latin 18
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
Y 13
72.2%
N 5
 
27.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 18
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
Y 13
72.2%
N 5
 
27.8%

grade9swdfilledflag7
Text

MISSING 

Distinct2
Distinct (%)18.2%
Missing429
Missing (%)97.5%
Memory size14.2 KiB
2023-12-09T22:08:36.017833image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters11
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowY
2nd rowY
3rd rowN
4th rowN
5th rowY
ValueCountFrequency (%)
n 6
54.5%
y 5
45.5%
2023-12-09T22:08:36.246686image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 6
54.5%
Y 5
45.5%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 11
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N 6
54.5%
Y 5
45.5%

Most occurring scripts

ValueCountFrequency (%)
Latin 11
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 6
54.5%
Y 5
45.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 6
54.5%
Y 5
45.5%

grade9swdfilledflag8
Text

MISSING 

Distinct2
Distinct (%)100.0%
Missing438
Missing (%)99.5%
Memory size13.9 KiB
2023-12-09T22:08:36.361783image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters2
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st rowN
2nd rowY
ValueCountFrequency (%)
y 1
50.0%
n 1
50.0%
2023-12-09T22:08:36.589694image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
Y 1
50.0%
N 1
50.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 2
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
Y 1
50.0%
N 1
50.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
Y 1
50.0%
N 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
Y 1
50.0%
N 1
50.0%

grade9swdfilledflag9
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing439
Missing (%)99.8%
Memory size13.9 KiB
2023-12-09T22:08:36.696151image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowY
ValueCountFrequency (%)
y 1
100.0%
2023-12-09T22:08:36.918442image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
Y 1
100.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 1
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
Y 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
Y 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
Y 1
100.0%

grade9swdfilledflag10
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing440
Missing (%)100.0%
Memory size3.6 KiB

grade9swdapplicants1
Text

MISSING 

Distinct211
Distinct (%)50.2%
Missing20
Missing (%)4.5%
Memory size25.1 KiB
2023-12-09T22:08:37.436575image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.452380952
Min length1

Characters and Unicode

Total characters1030
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique107 ?
Unique (%)25.5%

Sample

1st row138
2nd row52
3rd row53
4th row46
5th row62
ValueCountFrequency (%)
93 7
 
1.7%
74 6
 
1.4%
53 6
 
1.4%
105 6
 
1.4%
91 6
 
1.4%
66 6
 
1.4%
52 6
 
1.4%
62 5
 
1.2%
122 5
 
1.2%
76 5
 
1.2%
Other values (201) 362
86.2%
2023-12-09T22:08:38.124140image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 204
19.8%
2 130
12.6%
3 111
10.8%
4 98
9.5%
5 94
9.1%
7 83
8.1%
6 83
8.1%
9 82
8.0%
0 73
 
7.1%
8 72
 
7.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1030
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 204
19.8%
2 130
12.6%
3 111
10.8%
4 98
9.5%
5 94
9.1%
7 83
8.1%
6 83
8.1%
9 82
8.0%
0 73
 
7.1%
8 72
 
7.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1030
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 204
19.8%
2 130
12.6%
3 111
10.8%
4 98
9.5%
5 94
9.1%
7 83
8.1%
6 83
8.1%
9 82
8.0%
0 73
 
7.1%
8 72
 
7.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1030
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 204
19.8%
2 130
12.6%
3 111
10.8%
4 98
9.5%
5 94
9.1%
7 83
8.1%
6 83
8.1%
9 82
8.0%
0 73
 
7.1%
8 72
 
7.0%

grade9swdapplicants2
Text

MISSING 

Distinct76
Distinct (%)67.9%
Missing328
Missing (%)74.5%
Memory size16.8 KiB
2023-12-09T22:08:38.458905image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.125
Min length1

Characters and Unicode

Total characters238
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique51 ?
Unique (%)45.5%

Sample

1st row36
2nd row36
3rd row66
4th row118
5th row29
ValueCountFrequency (%)
36 5
 
4.5%
23 4
 
3.6%
26 4
 
3.6%
2 3
 
2.7%
28 3
 
2.7%
17 3
 
2.7%
66 3
 
2.7%
35 2
 
1.8%
134 2
 
1.8%
19 2
 
1.8%
Other values (66) 81
72.3%
2023-12-09T22:08:38.902326image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 46
19.3%
2 36
15.1%
3 30
12.6%
6 29
12.2%
4 25
10.5%
7 19
8.0%
5 19
8.0%
0 12
 
5.0%
8 11
 
4.6%
9 11
 
4.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 238
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 46
19.3%
2 36
15.1%
3 30
12.6%
6 29
12.2%
4 25
10.5%
7 19
8.0%
5 19
8.0%
0 12
 
5.0%
8 11
 
4.6%
9 11
 
4.6%

Most occurring scripts

ValueCountFrequency (%)
Common 238
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 46
19.3%
2 36
15.1%
3 30
12.6%
6 29
12.2%
4 25
10.5%
7 19
8.0%
5 19
8.0%
0 12
 
5.0%
8 11
 
4.6%
9 11
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 238
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 46
19.3%
2 36
15.1%
3 30
12.6%
6 29
12.2%
4 25
10.5%
7 19
8.0%
5 19
8.0%
0 12
 
5.0%
8 11
 
4.6%
9 11
 
4.6%

grade9swdapplicants3
Text

MISSING 

Distinct42
Distinct (%)66.7%
Missing377
Missing (%)85.7%
Memory size15.5 KiB
2023-12-09T22:08:39.189960image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.063492063
Min length1

Characters and Unicode

Total characters130
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique26 ?
Unique (%)41.3%

Sample

1st row23
2nd row23
3rd row54
4th row124
5th row16
ValueCountFrequency (%)
23 3
 
4.8%
40 3
 
4.8%
14 3
 
4.8%
20 3
 
4.8%
32 3
 
4.8%
62 2
 
3.2%
30 2
 
3.2%
28 2
 
3.2%
67 2
 
3.2%
39 2
 
3.2%
Other values (32) 38
60.3%
2023-12-09T22:08:40.793789image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 19
14.6%
3 18
13.8%
1 17
13.1%
4 16
12.3%
0 15
11.5%
6 14
10.8%
5 10
7.7%
7 9
6.9%
9 8
6.2%
8 4
 
3.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 130
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 19
14.6%
3 18
13.8%
1 17
13.1%
4 16
12.3%
0 15
11.5%
6 14
10.8%
5 10
7.7%
7 9
6.9%
9 8
6.2%
8 4
 
3.1%

Most occurring scripts

ValueCountFrequency (%)
Common 130
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 19
14.6%
3 18
13.8%
1 17
13.1%
4 16
12.3%
0 15
11.5%
6 14
10.8%
5 10
7.7%
7 9
6.9%
9 8
6.2%
8 4
 
3.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 130
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 19
14.6%
3 18
13.8%
1 17
13.1%
4 16
12.3%
0 15
11.5%
6 14
10.8%
5 10
7.7%
7 9
6.9%
9 8
6.2%
8 4
 
3.1%

grade9swdapplicants4
Text

MISSING 

Distinct37
Distinct (%)80.4%
Missing394
Missing (%)89.5%
Memory size15.1 KiB
2023-12-09T22:08:41.035132image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length1.97826087
Min length1

Characters and Unicode

Total characters91
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique30 ?
Unique (%)65.2%

Sample

1st row31
2nd row18
3rd row19
4th row57
5th row6
ValueCountFrequency (%)
26 4
 
8.7%
43 2
 
4.3%
28 2
 
4.3%
3 2
 
4.3%
33 2
 
4.3%
45 2
 
4.3%
22 2
 
4.3%
59 1
 
2.2%
57 1
 
2.2%
44 1
 
2.2%
Other values (27) 27
58.7%
2023-12-09T22:08:41.414609image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 18
19.8%
3 15
16.5%
6 11
12.1%
1 11
12.1%
4 10
11.0%
8 7
 
7.7%
5 7
 
7.7%
9 5
 
5.5%
7 4
 
4.4%
0 3
 
3.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 91
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 18
19.8%
3 15
16.5%
6 11
12.1%
1 11
12.1%
4 10
11.0%
8 7
 
7.7%
5 7
 
7.7%
9 5
 
5.5%
7 4
 
4.4%
0 3
 
3.3%

Most occurring scripts

ValueCountFrequency (%)
Common 91
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 18
19.8%
3 15
16.5%
6 11
12.1%
1 11
12.1%
4 10
11.0%
8 7
 
7.7%
5 7
 
7.7%
9 5
 
5.5%
7 4
 
4.4%
0 3
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 91
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 18
19.8%
3 15
16.5%
6 11
12.1%
1 11
12.1%
4 10
11.0%
8 7
 
7.7%
5 7
 
7.7%
9 5
 
5.5%
7 4
 
4.4%
0 3
 
3.3%

grade9swdapplicants5
Text

MISSING 

Distinct26
Distinct (%)83.9%
Missing409
Missing (%)93.0%
Memory size14.7 KiB
2023-12-09T22:08:41.627965image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2
Min length1

Characters and Unicode

Total characters62
Distinct characters9
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique22 ?
Unique (%)71.0%

Sample

1st row27
2nd row65
3rd row20
4th row23
5th row36
ValueCountFrequency (%)
27 3
 
9.7%
31 2
 
6.5%
63 2
 
6.5%
45 2
 
6.5%
36 1
 
3.2%
43 1
 
3.2%
13 1
 
3.2%
60 1
 
3.2%
20 1
 
3.2%
17 1
 
3.2%
Other values (16) 16
51.6%
2023-12-09T22:08:41.979468image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 12
19.4%
4 8
12.9%
1 8
12.9%
6 8
12.9%
7 7
11.3%
5 7
11.3%
2 5
8.1%
0 4
 
6.5%
8 3
 
4.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 62
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 12
19.4%
4 8
12.9%
1 8
12.9%
6 8
12.9%
7 7
11.3%
5 7
11.3%
2 5
8.1%
0 4
 
6.5%
8 3
 
4.8%

Most occurring scripts

ValueCountFrequency (%)
Common 62
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 12
19.4%
4 8
12.9%
1 8
12.9%
6 8
12.9%
7 7
11.3%
5 7
11.3%
2 5
8.1%
0 4
 
6.5%
8 3
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 62
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 12
19.4%
4 8
12.9%
1 8
12.9%
6 8
12.9%
7 7
11.3%
5 7
11.3%
2 5
8.1%
0 4
 
6.5%
8 3
 
4.8%

grade9swdapplicants6
Text

MISSING 

Distinct18
Distinct (%)100.0%
Missing422
Missing (%)95.9%
Memory size14.4 KiB
2023-12-09T22:08:42.219367image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.166666667
Min length2

Characters and Unicode

Total characters39
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique18 ?
Unique (%)100.0%

Sample

1st row19
2nd row57
3rd row55
4th row107
5th row51
ValueCountFrequency (%)
39 1
 
5.6%
63 1
 
5.6%
107 1
 
5.6%
68 1
 
5.6%
20 1
 
5.6%
19 1
 
5.6%
33 1
 
5.6%
70 1
 
5.6%
57 1
 
5.6%
71 1
 
5.6%
Other values (8) 8
44.4%
2023-12-09T22:08:42.581343image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 7
17.9%
1 6
15.4%
5 5
12.8%
6 4
10.3%
4 4
10.3%
0 4
10.3%
7 4
10.3%
9 2
 
5.1%
8 2
 
5.1%
2 1
 
2.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 39
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 7
17.9%
1 6
15.4%
5 5
12.8%
6 4
10.3%
4 4
10.3%
0 4
10.3%
7 4
10.3%
9 2
 
5.1%
8 2
 
5.1%
2 1
 
2.6%

Most occurring scripts

ValueCountFrequency (%)
Common 39
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 7
17.9%
1 6
15.4%
5 5
12.8%
6 4
10.3%
4 4
10.3%
0 4
10.3%
7 4
10.3%
9 2
 
5.1%
8 2
 
5.1%
2 1
 
2.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 39
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 7
17.9%
1 6
15.4%
5 5
12.8%
6 4
10.3%
4 4
10.3%
0 4
10.3%
7 4
10.3%
9 2
 
5.1%
8 2
 
5.1%
2 1
 
2.6%

grade9swdapplicants7
Text

MISSING 

Distinct11
Distinct (%)100.0%
Missing429
Missing (%)97.5%
Memory size14.2 KiB
2023-12-09T22:08:42.784766image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length2
Mean length1.909090909
Min length1

Characters and Unicode

Total characters21
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique11 ?
Unique (%)100.0%

Sample

1st row79
2nd row43
3rd row25
4th row15
5th row27
ValueCountFrequency (%)
43 1
9.1%
79 1
9.1%
26 1
9.1%
41 1
9.1%
58 1
9.1%
30 1
9.1%
15 1
9.1%
53 1
9.1%
27 1
9.1%
25 1
9.1%
2023-12-09T22:08:43.108917image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 4
19.0%
3 3
14.3%
2 3
14.3%
4 2
9.5%
7 2
9.5%
6 2
9.5%
1 2
9.5%
9 1
 
4.8%
8 1
 
4.8%
0 1
 
4.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 21
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 4
19.0%
3 3
14.3%
2 3
14.3%
4 2
9.5%
7 2
9.5%
6 2
9.5%
1 2
9.5%
9 1
 
4.8%
8 1
 
4.8%
0 1
 
4.8%

Most occurring scripts

ValueCountFrequency (%)
Common 21
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 4
19.0%
3 3
14.3%
2 3
14.3%
4 2
9.5%
7 2
9.5%
6 2
9.5%
1 2
9.5%
9 1
 
4.8%
8 1
 
4.8%
0 1
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 21
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 4
19.0%
3 3
14.3%
2 3
14.3%
4 2
9.5%
7 2
9.5%
6 2
9.5%
1 2
9.5%
9 1
 
4.8%
8 1
 
4.8%
0 1
 
4.8%

grade9swdapplicants8
Text

MISSING 

Distinct2
Distinct (%)100.0%
Missing438
Missing (%)99.5%
Memory size13.9 KiB
2023-12-09T22:08:43.258440image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters4
Distinct characters4
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st row12
2nd row74
ValueCountFrequency (%)
74 1
50.0%
12 1
50.0%
2023-12-09T22:08:43.514478image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7 1
25.0%
4 1
25.0%
1 1
25.0%
2 1
25.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
7 1
25.0%
4 1
25.0%
1 1
25.0%
2 1
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
7 1
25.0%
4 1
25.0%
1 1
25.0%
2 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7 1
25.0%
4 1
25.0%
1 1
25.0%
2 1
25.0%

grade9swdapplicants9
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing439
Missing (%)99.8%
Memory size13.9 KiB
2023-12-09T22:08:43.620957image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters2
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row63
ValueCountFrequency (%)
63 1
100.0%
2023-12-09T22:08:43.845844image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6 1
50.0%
3 1
50.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
6 1
50.0%
3 1
50.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
6 1
50.0%
3 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6 1
50.0%
3 1
50.0%

grade9swdapplicants10
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing440
Missing (%)100.0%
Memory size3.6 KiB

seats1specialized
Text

MISSING 

Distinct9
Distinct (%)100.0%
Missing431
Missing (%)98.0%
Memory size14.1 KiB
2023-12-09T22:08:44.038350image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length4
Median length3
Mean length2.888888889
Min length2

Characters and Unicode

Total characters26
Distinct characters8
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9 ?
Unique (%)100.0%

Sample

1st row104
2nd row750
3rd row300
4th row59
5th row150
ValueCountFrequency (%)
1400 1
11.1%
150 1
11.1%
104 1
11.1%
59 1
11.1%
750 1
11.1%
300 1
11.1%
814 1
11.1%
110 1
11.1%
90 1
11.1%
2023-12-09T22:08:44.375572image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 9
34.6%
1 6
23.1%
4 3
 
11.5%
5 3
 
11.5%
9 2
 
7.7%
7 1
 
3.8%
3 1
 
3.8%
8 1
 
3.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 26
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 9
34.6%
1 6
23.1%
4 3
 
11.5%
5 3
 
11.5%
9 2
 
7.7%
7 1
 
3.8%
3 1
 
3.8%
8 1
 
3.8%

Most occurring scripts

ValueCountFrequency (%)
Common 26
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 9
34.6%
1 6
23.1%
4 3
 
11.5%
5 3
 
11.5%
9 2
 
7.7%
7 1
 
3.8%
3 1
 
3.8%
8 1
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 26
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 9
34.6%
1 6
23.1%
4 3
 
11.5%
5 3
 
11.5%
9 2
 
7.7%
7 1
 
3.8%
3 1
 
3.8%
8 1
 
3.8%

seats2specialized
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing439
Missing (%)99.8%
Memory size13.9 KiB
2023-12-09T22:08:44.496305image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters3
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row118
ValueCountFrequency (%)
118 1
100.0%
2023-12-09T22:08:44.732022image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 2
66.7%
8 1
33.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 2
66.7%
8 1
33.3%

Most occurring scripts

ValueCountFrequency (%)
Common 3
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 2
66.7%
8 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 2
66.7%
8 1
33.3%

seats3specialized
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing439
Missing (%)99.8%
Memory size13.9 KiB
2023-12-09T22:08:44.853560image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters3
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row181
ValueCountFrequency (%)
181 1
100.0%
2023-12-09T22:08:45.094869image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 2
66.7%
8 1
33.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 2
66.7%
8 1
33.3%

Most occurring scripts

ValueCountFrequency (%)
Common 3
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 2
66.7%
8 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 2
66.7%
8 1
33.3%

seats4specialized
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing439
Missing (%)99.8%
Memory size13.9 KiB
2023-12-09T22:08:45.202732image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters2
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row28
ValueCountFrequency (%)
28 1
100.0%
2023-12-09T22:08:45.425783image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 1
50.0%
8 1
50.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 1
50.0%
8 1
50.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 1
50.0%
8 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 1
50.0%
8 1
50.0%

seats5specialized
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing439
Missing (%)99.8%
Memory size13.9 KiB
2023-12-09T22:08:45.534994image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters2
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row99
ValueCountFrequency (%)
99 1
100.0%
2023-12-09T22:08:45.756827image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9 2
100.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
9 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
9 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
9 2
100.0%

seats6specialized
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing439
Missing (%)99.8%
Memory size13.9 KiB
2023-12-09T22:08:45.874263image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters3
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row211
ValueCountFrequency (%)
211 1
100.0%
2023-12-09T22:08:46.105723image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 2
66.7%
2 1
33.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 2
66.7%
2 1
33.3%

Most occurring scripts

ValueCountFrequency (%)
Common 3
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 2
66.7%
2 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 2
66.7%
2 1
33.3%

applicants1specialized
Text

MISSING 

Distinct9
Distinct (%)100.0%
Missing431
Missing (%)98.0%
Memory size14.1 KiB
2023-12-09T22:08:46.304066image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length5
Median length5
Mean length4.888888889
Min length4

Characters and Unicode

Total characters44
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9 ?
Unique (%)100.0%

Sample

1st row16592
2nd row19456
3rd row15490
4th row2006
5th row16962
ValueCountFrequency (%)
15490 1
11.1%
16962 1
11.1%
2006 1
11.1%
22476 1
11.1%
17061 1
11.1%
19308 1
11.1%
19456 1
11.1%
16592 1
11.1%
23169 1
11.1%
2023-12-09T22:08:46.635748image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 8
18.2%
6 8
18.2%
9 6
13.6%
2 6
13.6%
0 5
11.4%
5 3
 
6.8%
4 3
 
6.8%
7 2
 
4.5%
3 2
 
4.5%
8 1
 
2.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 44
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 8
18.2%
6 8
18.2%
9 6
13.6%
2 6
13.6%
0 5
11.4%
5 3
 
6.8%
4 3
 
6.8%
7 2
 
4.5%
3 2
 
4.5%
8 1
 
2.3%

Most occurring scripts

ValueCountFrequency (%)
Common 44
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 8
18.2%
6 8
18.2%
9 6
13.6%
2 6
13.6%
0 5
11.4%
5 3
 
6.8%
4 3
 
6.8%
7 2
 
4.5%
3 2
 
4.5%
8 1
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 44
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 8
18.2%
6 8
18.2%
9 6
13.6%
2 6
13.6%
0 5
11.4%
5 3
 
6.8%
4 3
 
6.8%
7 2
 
4.5%
3 2
 
4.5%
8 1
 
2.3%

applicants2specialized
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing439
Missing (%)99.8%
Memory size13.9 KiB
2023-12-09T22:08:46.775089image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length4
Median length4
Mean length4
Min length4

Characters and Unicode

Total characters4
Distinct characters3
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row1541
ValueCountFrequency (%)
1541 1
100.0%
2023-12-09T22:08:47.022814image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 2
50.0%
5 1
25.0%
4 1
25.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 2
50.0%
5 1
25.0%
4 1
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 2
50.0%
5 1
25.0%
4 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 2
50.0%
5 1
25.0%
4 1
25.0%

applicants3specialized
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing439
Missing (%)99.8%
Memory size13.9 KiB
2023-12-09T22:08:47.156563image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length4
Median length4
Mean length4
Min length4

Characters and Unicode

Total characters4
Distinct characters4
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row3067
ValueCountFrequency (%)
3067 1
100.0%
2023-12-09T22:08:47.418242image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 1
25.0%
0 1
25.0%
6 1
25.0%
7 1
25.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 1
25.0%
0 1
25.0%
6 1
25.0%
7 1
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 1
25.0%
0 1
25.0%
6 1
25.0%
7 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 1
25.0%
0 1
25.0%
6 1
25.0%
7 1
25.0%

applicants4specialized
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing439
Missing (%)99.8%
Memory size13.9 KiB
2023-12-09T22:08:47.538802image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters3
Distinct characters3
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row536
ValueCountFrequency (%)
536 1
100.0%
2023-12-09T22:08:47.773262image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 1
33.3%
3 1
33.3%
6 1
33.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 1
33.3%
3 1
33.3%
6 1
33.3%

Most occurring scripts

ValueCountFrequency (%)
Common 3
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 1
33.3%
3 1
33.3%
6 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 1
33.3%
3 1
33.3%
6 1
33.3%

applicants5specialized
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing439
Missing (%)99.8%
Memory size13.9 KiB
2023-12-09T22:08:47.912801image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length4
Median length4
Mean length4
Min length4

Characters and Unicode

Total characters4
Distinct characters3
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row2616
ValueCountFrequency (%)
2616 1
100.0%
2023-12-09T22:08:48.177489image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6 2
50.0%
2 1
25.0%
1 1
25.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
6 2
50.0%
2 1
25.0%
1 1
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
6 2
50.0%
2 1
25.0%
1 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6 2
50.0%
2 1
25.0%
1 1
25.0%

applicants6specialized
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing439
Missing (%)99.8%
Memory size13.9 KiB
2023-12-09T22:08:48.314695image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length4
Median length4
Mean length4
Min length4

Characters and Unicode

Total characters4
Distinct characters3
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row2429
ValueCountFrequency (%)
2429 1
100.0%
2023-12-09T22:08:48.557471image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 2
50.0%
4 1
25.0%
9 1
25.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 2
50.0%
4 1
25.0%
9 1
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 2
50.0%
4 1
25.0%
9 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 2
50.0%
4 1
25.0%
9 1
25.0%

appperseat1specialized
Text

MISSING 

Distinct9
Distinct (%)100.0%
Missing431
Missing (%)98.0%
Memory size14.1 KiB
2023-12-09T22:08:48.752258image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.444444444
Min length2

Characters and Unicode

Total characters22
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9 ?
Unique (%)100.0%

Sample

1st row160
2nd row26
3rd row52
4th row34
5th row113
ValueCountFrequency (%)
28 1
11.1%
17 1
11.1%
52 1
11.1%
26 1
11.1%
34 1
11.1%
113 1
11.1%
176 1
11.1%
190 1
11.1%
160 1
11.1%
2023-12-09T22:08:49.081718image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 6
27.3%
2 3
13.6%
6 3
13.6%
7 2
 
9.1%
3 2
 
9.1%
0 2
 
9.1%
8 1
 
4.5%
5 1
 
4.5%
4 1
 
4.5%
9 1
 
4.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 22
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 6
27.3%
2 3
13.6%
6 3
13.6%
7 2
 
9.1%
3 2
 
9.1%
0 2
 
9.1%
8 1
 
4.5%
5 1
 
4.5%
4 1
 
4.5%
9 1
 
4.5%

Most occurring scripts

ValueCountFrequency (%)
Common 22
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 6
27.3%
2 3
13.6%
6 3
13.6%
7 2
 
9.1%
3 2
 
9.1%
0 2
 
9.1%
8 1
 
4.5%
5 1
 
4.5%
4 1
 
4.5%
9 1
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 22
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 6
27.3%
2 3
13.6%
6 3
13.6%
7 2
 
9.1%
3 2
 
9.1%
0 2
 
9.1%
8 1
 
4.5%
5 1
 
4.5%
4 1
 
4.5%
9 1
 
4.5%

appperseat2specialized
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing439
Missing (%)99.8%
Memory size13.9 KiB
2023-12-09T22:08:49.191890image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters2
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row13
ValueCountFrequency (%)
13 1
100.0%
2023-12-09T22:08:49.411705image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 1
50.0%
3 1
50.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 1
50.0%
3 1
50.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 1
50.0%
3 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 1
50.0%
3 1
50.0%

appperseat3specialized
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing439
Missing (%)99.8%
Memory size13.9 KiB
2023-12-09T22:08:49.521482image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters2
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row17
ValueCountFrequency (%)
17 1
100.0%
2023-12-09T22:08:49.755484image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 1
50.0%
7 1
50.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 1
50.0%
7 1
50.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 1
50.0%
7 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 1
50.0%
7 1
50.0%

appperseat4specialized
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing439
Missing (%)99.8%
Memory size13.9 KiB
2023-12-09T22:08:49.866676image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters2
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row19
ValueCountFrequency (%)
19 1
100.0%
2023-12-09T22:08:50.105315image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 1
50.0%
9 1
50.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 1
50.0%
9 1
50.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 1
50.0%
9 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 1
50.0%
9 1
50.0%

appperseat5specialized
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing439
Missing (%)99.8%
Memory size13.9 KiB
2023-12-09T22:08:50.213869image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters2
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row26
ValueCountFrequency (%)
26 1
100.0%
2023-12-09T22:08:50.502985image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 1
50.0%
6 1
50.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 1
50.0%
6 1
50.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 1
50.0%
6 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 1
50.0%
6 1
50.0%

appperseat6specialized
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing439
Missing (%)99.8%
Memory size13.9 KiB
2023-12-09T22:08:50.609243image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters2
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row12
ValueCountFrequency (%)
12 1
100.0%
2023-12-09T22:08:50.829754image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 1
50.0%
2 1
50.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 1
50.0%
2 1
50.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 1
50.0%
2 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 1
50.0%
2 1
50.0%

seats101
Text

Distinct42
Distinct (%)9.5%
Missing0
Missing (%)0.0%
Memory size28.9 KiB
2023-12-09T22:08:51.055942image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length9
Median length7
Mean length4.568181818
Min length2

Characters and Unicode

Total characters2010
Distinct characters20
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique19 ?
Unique (%)4.3%

Sample

1st rowYes–9
2nd rowYes-New
3rd rowNo
4th rowYes-50
5th rowNo
ValueCountFrequency (%)
no 155
34.9%
yes-10 90
20.3%
yes-5 49
 
11.0%
yesâ–5 29
 
6.5%
yesâ–10 24
 
5.4%
yes-20 12
 
2.7%
yes-new 11
 
2.5%
yes-15 9
 
2.0%
yes-8 6
 
1.4%
yesâ–15 4
 
0.9%
Other values (33) 55
 
12.4%
2023-12-09T22:08:51.430287image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 298
14.8%
Y 285
14.2%
s 285
14.2%
- 209
10.4%
N 168
8.4%
o 155
7.7%
1 138
6.9%
0 138
6.9%
5 99
 
4.9%
– 75
 
3.7%
Other values (10) 160
8.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 751
37.4%
Uppercase Letter 528
26.3%
Decimal Number 443
22.0%
Dash Punctuation 284
 
14.1%
Space Separator 4
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 138
31.2%
0 138
31.2%
5 99
22.3%
2 27
 
6.1%
3 14
 
3.2%
4 10
 
2.3%
8 9
 
2.0%
6 5
 
1.1%
7 2
 
0.5%
9 1
 
0.2%
Lowercase Letter
ValueCountFrequency (%)
e 298
39.7%
s 285
37.9%
o 155
20.6%
w 13
 
1.7%
Uppercase Letter
ValueCountFrequency (%)
Y 285
54.0%
N 168
31.8%
 75
 
14.2%
Dash Punctuation
ValueCountFrequency (%)
- 209
73.6%
– 75
 
26.4%
Space Separator
ValueCountFrequency (%)
4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1279
63.6%
Common 731
36.4%

Most frequent character per script

Common
ValueCountFrequency (%)
- 209
28.6%
1 138
18.9%
0 138
18.9%
5 99
13.5%
– 75
 
10.3%
2 27
 
3.7%
3 14
 
1.9%
4 10
 
1.4%
8 9
 
1.2%
6 5
 
0.7%
Other values (3) 7
 
1.0%
Latin
ValueCountFrequency (%)
e 298
23.3%
Y 285
22.3%
s 285
22.3%
N 168
13.1%
o 155
12.1%
 75
 
5.9%
w 13
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1860
92.5%
Punctuation 75
 
3.7%
None 75
 
3.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 298
16.0%
Y 285
15.3%
s 285
15.3%
- 209
11.2%
N 168
9.0%
o 155
8.3%
1 138
7.4%
0 138
7.4%
5 99
 
5.3%
2 27
 
1.5%
Other values (8) 58
 
3.1%
Punctuation
ValueCountFrequency (%)
– 75
100.0%
None
ValueCountFrequency (%)
 75
100.0%

seats102
Text

MISSING 

Distinct21
Distinct (%)16.4%
Missing312
Missing (%)70.9%
Memory size17.5 KiB
2023-12-09T22:08:51.624664image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length9
Median length7
Mean length4.2421875
Min length2

Characters and Unicode

Total characters543
Distinct characters17
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10 ?
Unique (%)7.8%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowYes-5
5th rowNo
ValueCountFrequency (%)
no 50
38.5%
yes-10 24
18.5%
yes-5 23
17.7%
yes-20 5
 
3.8%
yes-new 3
 
2.3%
yes-30 3
 
2.3%
yes-24 2
 
1.5%
yes-6 2
 
1.5%
yes-2 2
 
1.5%
yes-15 2
 
1.5%
Other values (12) 14
 
10.8%
2023-12-09T22:08:51.962748image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 82
15.1%
Y 78
14.4%
s 78
14.4%
- 77
14.2%
N 54
9.9%
o 50
9.2%
0 33
6.1%
1 30
 
5.5%
5 28
 
5.2%
2 12
 
2.2%
Other values (7) 21
 
3.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 214
39.4%
Uppercase Letter 132
24.3%
Decimal Number 118
21.7%
Dash Punctuation 77
 
14.2%
Space Separator 2
 
0.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 33
28.0%
1 30
25.4%
5 28
23.7%
2 12
 
10.2%
4 6
 
5.1%
3 5
 
4.2%
6 2
 
1.7%
9 1
 
0.8%
7 1
 
0.8%
Lowercase Letter
ValueCountFrequency (%)
e 82
38.3%
s 78
36.4%
o 50
23.4%
w 4
 
1.9%
Uppercase Letter
ValueCountFrequency (%)
Y 78
59.1%
N 54
40.9%
Dash Punctuation
ValueCountFrequency (%)
- 77
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 346
63.7%
Common 197
36.3%

Most frequent character per script

Common
ValueCountFrequency (%)
- 77
39.1%
0 33
16.8%
1 30
 
15.2%
5 28
 
14.2%
2 12
 
6.1%
4 6
 
3.0%
3 5
 
2.5%
6 2
 
1.0%
2
 
1.0%
9 1
 
0.5%
Latin
ValueCountFrequency (%)
e 82
23.7%
Y 78
22.5%
s 78
22.5%
N 54
15.6%
o 50
14.5%
w 4
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 543
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 82
15.1%
Y 78
14.4%
s 78
14.4%
- 77
14.2%
N 54
9.9%
o 50
9.2%
0 33
6.1%
1 30
 
5.5%
5 28
 
5.2%
2 12
 
2.2%
Other values (7) 21
 
3.9%

seats103
Text

MISSING 

Distinct12
Distinct (%)17.1%
Missing370
Missing (%)84.1%
Memory size15.9 KiB
2023-12-09T22:08:52.167795image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length7
Median length6
Mean length4.5
Min length2

Characters and Unicode

Total characters315
Distinct characters14
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)7.1%

Sample

1st rowYes
2nd rowYes-5
3rd rowYes-5
4th rowNo
5th rowYes-10
ValueCountFrequency (%)
no 20
28.6%
yes-10 19
27.1%
yes-5 15
21.4%
yes-20 4
 
5.7%
yes 3
 
4.3%
yes-15 2
 
2.9%
yes-2 2
 
2.9%
yes-29 1
 
1.4%
yes-16 1
 
1.4%
yes-50 1
 
1.4%
Other values (2) 2
 
2.9%
2023-12-09T22:08:52.498198image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 51
16.2%
Y 50
15.9%
s 50
15.9%
- 47
14.9%
0 25
7.9%
1 22
7.0%
N 21
6.7%
o 20
 
6.3%
5 18
 
5.7%
2 7
 
2.2%
Other values (4) 4
 
1.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 122
38.7%
Decimal Number 75
23.8%
Uppercase Letter 71
22.5%
Dash Punctuation 47
 
14.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 25
33.3%
1 22
29.3%
5 18
24.0%
2 7
 
9.3%
9 1
 
1.3%
6 1
 
1.3%
3 1
 
1.3%
Lowercase Letter
ValueCountFrequency (%)
e 51
41.8%
s 50
41.0%
o 20
 
16.4%
w 1
 
0.8%
Uppercase Letter
ValueCountFrequency (%)
Y 50
70.4%
N 21
29.6%
Dash Punctuation
ValueCountFrequency (%)
- 47
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 193
61.3%
Common 122
38.7%

Most frequent character per script

Common
ValueCountFrequency (%)
- 47
38.5%
0 25
20.5%
1 22
18.0%
5 18
 
14.8%
2 7
 
5.7%
9 1
 
0.8%
6 1
 
0.8%
3 1
 
0.8%
Latin
ValueCountFrequency (%)
e 51
26.4%
Y 50
25.9%
s 50
25.9%
N 21
10.9%
o 20
 
10.4%
w 1
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 315
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 51
16.2%
Y 50
15.9%
s 50
15.9%
- 47
14.9%
0 25
7.9%
1 22
7.0%
N 21
6.7%
o 20
 
6.3%
5 18
 
5.7%
2 7
 
2.2%
Other values (4) 4
 
1.3%

seats104
Text

MISSING 

Distinct9
Distinct (%)17.0%
Missing387
Missing (%)88.0%
Memory size15.4 KiB
2023-12-09T22:08:52.696322image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length6
Median length5
Mean length4.339622642
Min length2

Characters and Unicode

Total characters230
Distinct characters12
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)5.7%

Sample

1st rowYes-2
2nd rowYes-5
3rd rowNo
4th rowYes-10
5th rowYes-5
ValueCountFrequency (%)
no 15
28.3%
yes-10 14
26.4%
yes-5 10
18.9%
yes 5
 
9.4%
yes-20 4
 
7.5%
yes-2 2
 
3.8%
yes-30 1
 
1.9%
yes-12 1
 
1.9%
yes-7 1
 
1.9%
2023-12-09T22:08:53.035380image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
Y 38
16.5%
e 38
16.5%
s 38
16.5%
- 33
14.3%
0 19
8.3%
N 15
 
6.5%
o 15
 
6.5%
1 15
 
6.5%
5 10
 
4.3%
2 7
 
3.0%
Other values (2) 2
 
0.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 91
39.6%
Uppercase Letter 53
23.0%
Decimal Number 53
23.0%
Dash Punctuation 33
 
14.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 19
35.8%
1 15
28.3%
5 10
18.9%
2 7
 
13.2%
3 1
 
1.9%
7 1
 
1.9%
Lowercase Letter
ValueCountFrequency (%)
e 38
41.8%
s 38
41.8%
o 15
 
16.5%
Uppercase Letter
ValueCountFrequency (%)
Y 38
71.7%
N 15
 
28.3%
Dash Punctuation
ValueCountFrequency (%)
- 33
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 144
62.6%
Common 86
37.4%

Most frequent character per script

Common
ValueCountFrequency (%)
- 33
38.4%
0 19
22.1%
1 15
17.4%
5 10
 
11.6%
2 7
 
8.1%
3 1
 
1.2%
7 1
 
1.2%
Latin
ValueCountFrequency (%)
Y 38
26.4%
e 38
26.4%
s 38
26.4%
N 15
 
10.4%
o 15
 
10.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 230
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
Y 38
16.5%
e 38
16.5%
s 38
16.5%
- 33
14.3%
0 19
8.3%
N 15
 
6.5%
o 15
 
6.5%
1 15
 
6.5%
5 10
 
4.3%
2 7
 
3.0%
Other values (2) 2
 
0.9%

seats105
Text

MISSING 

Distinct10
Distinct (%)26.3%
Missing402
Missing (%)91.4%
Memory size15.0 KiB
2023-12-09T22:08:53.212487image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length9
Median length7
Mean length4.710526316
Min length2

Characters and Unicode

Total characters179
Distinct characters13
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)15.8%

Sample

1st rowYes-5
2nd rowYes-10
3rd rowNo
4th rowYes-10
5th rowYes
ValueCountFrequency (%)
yes-10 13
32.5%
no 8
20.0%
yes-5 7
17.5%
yes 5
 
12.5%
yes-2 1
 
2.5%
yes-20 1
 
2.5%
yes-50 1
 
2.5%
1
 
2.5%
new 1
 
2.5%
yes-7 1
 
2.5%
2023-12-09T22:08:53.537453image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 32
17.9%
Y 30
16.8%
s 30
16.8%
- 26
14.5%
0 15
8.4%
1 13
7.3%
N 10
 
5.6%
o 8
 
4.5%
5 8
 
4.5%
2 2
 
1.1%
Other values (3) 5
 
2.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 72
40.2%
Uppercase Letter 40
22.3%
Decimal Number 39
21.8%
Dash Punctuation 26
 
14.5%
Space Separator 2
 
1.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 15
38.5%
1 13
33.3%
5 8
20.5%
2 2
 
5.1%
7 1
 
2.6%
Lowercase Letter
ValueCountFrequency (%)
e 32
44.4%
s 30
41.7%
o 8
 
11.1%
w 2
 
2.8%
Uppercase Letter
ValueCountFrequency (%)
Y 30
75.0%
N 10
 
25.0%
Dash Punctuation
ValueCountFrequency (%)
- 26
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 112
62.6%
Common 67
37.4%

Most frequent character per script

Common
ValueCountFrequency (%)
- 26
38.8%
0 15
22.4%
1 13
19.4%
5 8
 
11.9%
2 2
 
3.0%
2
 
3.0%
7 1
 
1.5%
Latin
ValueCountFrequency (%)
e 32
28.6%
Y 30
26.8%
s 30
26.8%
N 10
 
8.9%
o 8
 
7.1%
w 2
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 179
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 32
17.9%
Y 30
16.8%
s 30
16.8%
- 26
14.5%
0 15
8.4%
1 13
7.3%
N 10
 
5.6%
o 8
 
4.5%
5 8
 
4.5%
2 2
 
1.1%
Other values (3) 5
 
2.8%

seats106
Text

MISSING 

Distinct5
Distinct (%)20.8%
Missing416
Missing (%)94.5%
Memory size14.6 KiB
2023-12-09T22:08:53.716953image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length6
Median length5
Mean length4.041666667
Min length2

Characters and Unicode

Total characters97
Distinct characters10
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowYes-5
2nd rowYes-10
3rd rowNo
4th rowYes-10
5th rowYes
ValueCountFrequency (%)
no 7
29.2%
yes-10 6
25.0%
yes 5
20.8%
yes-5 4
16.7%
yes-20 2
 
8.3%
2023-12-09T22:08:54.046116image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
Y 17
17.5%
e 17
17.5%
s 17
17.5%
- 12
12.4%
0 8
8.2%
N 7
7.2%
o 7
7.2%
1 6
 
6.2%
5 4
 
4.1%
2 2
 
2.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 41
42.3%
Uppercase Letter 24
24.7%
Decimal Number 20
20.6%
Dash Punctuation 12
 
12.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 8
40.0%
1 6
30.0%
5 4
20.0%
2 2
 
10.0%
Lowercase Letter
ValueCountFrequency (%)
e 17
41.5%
s 17
41.5%
o 7
17.1%
Uppercase Letter
ValueCountFrequency (%)
Y 17
70.8%
N 7
29.2%
Dash Punctuation
ValueCountFrequency (%)
- 12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 65
67.0%
Common 32
33.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
Y 17
26.2%
e 17
26.2%
s 17
26.2%
N 7
10.8%
o 7
10.8%
Common
ValueCountFrequency (%)
- 12
37.5%
0 8
25.0%
1 6
18.8%
5 4
 
12.5%
2 2
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 97
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
Y 17
17.5%
e 17
17.5%
s 17
17.5%
- 12
12.4%
0 8
8.2%
N 7
7.2%
o 7
7.2%
1 6
 
6.2%
5 4
 
4.1%
2 2
 
2.1%

seats107
Text

MISSING 

Distinct4
Distinct (%)28.6%
Missing426
Missing (%)96.8%
Memory size14.3 KiB
2023-12-09T22:08:54.214099image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length6
Median length3
Mean length3.642857143
Min length2

Characters and Unicode

Total characters51
Distinct characters9
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)7.1%

Sample

1st rowYes
2nd rowYes-10
3rd rowYes-10
4th rowYes-15
5th rowNo
ValueCountFrequency (%)
no 6
42.9%
yes-10 4
28.6%
yes 3
21.4%
yes-15 1
 
7.1%
2023-12-09T22:08:54.512146image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
Y 8
15.7%
e 8
15.7%
s 8
15.7%
N 6
11.8%
o 6
11.8%
- 5
9.8%
1 5
9.8%
0 4
7.8%
5 1
 
2.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 22
43.1%
Uppercase Letter 14
27.5%
Decimal Number 10
19.6%
Dash Punctuation 5
 
9.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 8
36.4%
s 8
36.4%
o 6
27.3%
Decimal Number
ValueCountFrequency (%)
1 5
50.0%
0 4
40.0%
5 1
 
10.0%
Uppercase Letter
ValueCountFrequency (%)
Y 8
57.1%
N 6
42.9%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 36
70.6%
Common 15
29.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
Y 8
22.2%
e 8
22.2%
s 8
22.2%
N 6
16.7%
o 6
16.7%
Common
ValueCountFrequency (%)
- 5
33.3%
1 5
33.3%
0 4
26.7%
5 1
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 51
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
Y 8
15.7%
e 8
15.7%
s 8
15.7%
N 6
11.8%
o 6
11.8%
- 5
9.8%
1 5
9.8%
0 4
7.8%
5 1
 
2.0%

seats108
Text

MISSING 

Distinct2
Distinct (%)28.6%
Missing433
Missing (%)98.4%
Memory size14.1 KiB
2023-12-09T22:08:54.638839image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.714285714
Min length2

Characters and Unicode

Total characters19
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowYes
2nd rowYes
3rd rowYes
4th rowNo
5th rowYes
ValueCountFrequency (%)
yes 5
71.4%
no 2
 
28.6%
2023-12-09T22:08:54.880907image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
Y 5
26.3%
e 5
26.3%
s 5
26.3%
N 2
 
10.5%
o 2
 
10.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 12
63.2%
Uppercase Letter 7
36.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 5
41.7%
s 5
41.7%
o 2
 
16.7%
Uppercase Letter
ValueCountFrequency (%)
Y 5
71.4%
N 2
 
28.6%

Most occurring scripts

ValueCountFrequency (%)
Latin 19
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
Y 5
26.3%
e 5
26.3%
s 5
26.3%
N 2
 
10.5%
o 2
 
10.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 19
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
Y 5
26.3%
e 5
26.3%
s 5
26.3%
N 2
 
10.5%
o 2
 
10.5%

seats109
Text

MISSING 

Distinct2
Distinct (%)100.0%
Missing438
Missing (%)99.5%
Memory size13.9 KiB
2023-12-09T22:08:55.025296image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2.5
Mean length2.5
Min length2

Characters and Unicode

Total characters5
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st rowNo
2nd rowYes
ValueCountFrequency (%)
yes 1
50.0%
no 1
50.0%
2023-12-09T22:08:55.294659image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
Y 1
20.0%
e 1
20.0%
s 1
20.0%
N 1
20.0%
o 1
20.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 3
60.0%
Uppercase Letter 2
40.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 1
33.3%
s 1
33.3%
o 1
33.3%
Uppercase Letter
ValueCountFrequency (%)
Y 1
50.0%
N 1
50.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 5
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
Y 1
20.0%
e 1
20.0%
s 1
20.0%
N 1
20.0%
o 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
Y 1
20.0%
e 1
20.0%
s 1
20.0%
N 1
20.0%
o 1
20.0%

seats1010
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing439
Missing (%)99.8%
Memory size13.9 KiB
2023-12-09T22:08:55.415604image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters3
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowYes
ValueCountFrequency (%)
yes 1
100.0%
2023-12-09T22:08:55.649399image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
Y 1
33.3%
e 1
33.3%
s 1
33.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2
66.7%
Uppercase Letter 1
33.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 1
50.0%
s 1
50.0%
Uppercase Letter
ValueCountFrequency (%)
Y 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 3
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
Y 1
33.3%
e 1
33.3%
s 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
Y 1
33.3%
e 1
33.3%
s 1
33.3%

admissionspriority11
Text

MISSING 

Distinct43
Distinct (%)10.8%
Missing42
Missing (%)9.5%
Memory size44.5 KiB
2023-12-09T22:08:55.898405image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length230
Median length110
Mean length53.62311558
Min length31

Characters and Unicode

Total characters21342
Distinct characters64
Distinct categories9 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique26 ?
Unique (%)6.5%

Sample

1st rowPriority to continuing 8th graders
2nd rowPriority to New York City residents who attend an information session
3rd rowPriority to Brooklyn students or residents
4th rowPriority to Queens students or residents who attend an information session
5th rowPriority to continuing 8th graders
ValueCountFrequency (%)
to 406
 
12.2%
priority 326
 
9.8%
residents 313
 
9.4%
students 198
 
5.9%
or 192
 
5.8%
who 179
 
5.4%
attend 175
 
5.2%
session 174
 
5.2%
an 174
 
5.2%
information 174
 
5.2%
Other values (99) 1028
30.8%
2023-12-09T22:08:56.347637image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2941
13.8%
t 2401
11.3%
o 1997
9.4%
n 1932
9.1%
i 1847
8.7%
r 1755
8.2%
s 1711
8.0%
e 1575
7.4%
d 799
 
3.7%
a 742
 
3.5%
Other values (54) 3642
17.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 17194
80.6%
Space Separator 2941
 
13.8%
Uppercase Letter 1038
 
4.9%
Decimal Number 151
 
0.7%
Other Punctuation 14
 
0.1%
Initial Punctuation 1
 
< 0.1%
Final Punctuation 1
 
< 0.1%
Open Punctuation 1
 
< 0.1%
Close Punctuation 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 2401
14.0%
o 1997
11.6%
n 1932
11.2%
i 1847
10.7%
r 1755
10.2%
s 1711
10.0%
e 1575
9.2%
d 799
 
4.6%
a 742
 
4.3%
y 486
 
2.8%
Other values (14) 1949
11.3%
Uppercase Letter
ValueCountFrequency (%)
P 329
31.7%
N 124
 
11.9%
Y 123
 
11.8%
C 123
 
11.8%
B 103
 
9.9%
O 72
 
6.9%
M 34
 
3.3%
Q 32
 
3.1%
D 27
 
2.6%
S 21
 
2.0%
Other values (12) 50
 
4.8%
Decimal Number
ValueCountFrequency (%)
8 77
51.0%
2 20
 
13.2%
1 17
 
11.3%
3 11
 
7.3%
6 8
 
5.3%
5 6
 
4.0%
0 5
 
3.3%
4 5
 
3.3%
7 1
 
0.7%
9 1
 
0.7%
Other Punctuation
ValueCountFrequency (%)
, 10
71.4%
& 2
 
14.3%
/ 2
 
14.3%
Space Separator
ValueCountFrequency (%)
2941
100.0%
Initial Punctuation
ValueCountFrequency (%)
“ 1
100.0%
Final Punctuation
ValueCountFrequency (%)
” 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 18232
85.4%
Common 3110
 
14.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 2401
13.2%
o 1997
11.0%
n 1932
10.6%
i 1847
10.1%
r 1755
9.6%
s 1711
9.4%
e 1575
8.6%
d 799
 
4.4%
a 742
 
4.1%
y 486
 
2.7%
Other values (36) 2987
16.4%
Common
ValueCountFrequency (%)
2941
94.6%
8 77
 
2.5%
2 20
 
0.6%
1 17
 
0.5%
3 11
 
0.4%
, 10
 
0.3%
6 8
 
0.3%
5 6
 
0.2%
0 5
 
0.2%
4 5
 
0.2%
Other values (8) 10
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 21338
> 99.9%
None 2
 
< 0.1%
Punctuation 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2941
13.8%
t 2401
11.3%
o 1997
9.4%
n 1932
9.1%
i 1847
8.7%
r 1755
8.2%
s 1711
8.0%
e 1575
7.4%
d 799
 
3.7%
a 742
 
3.5%
Other values (51) 3638
17.0%
None
ValueCountFrequency (%)
 2
100.0%
Punctuation
ValueCountFrequency (%)
“ 1
50.0%
” 1
50.0%

admissionspriority12
Text

MISSING 

Distinct18
Distinct (%)17.1%
Missing335
Missing (%)76.1%
Memory size21.0 KiB
2023-12-09T22:08:56.581690image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length100
Median length77
Mean length44.46666667
Min length31

Characters and Unicode

Total characters4669
Distinct characters44
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)5.7%

Sample

1st rowPriority to Queens students or residents
2nd rowPriority to continuing 8th graders
3rd rowOpen to New York City residents
4th rowPriority to Bronx students or residents
5th rowPriority to continuing 8th graders
ValueCountFrequency (%)
to 105
13.8%
residents 87
11.5%
priority 61
 
8.0%
new 48
 
6.3%
york 48
 
6.3%
city 48
 
6.3%
students 45
 
5.9%
open 40
 
5.3%
or 39
 
5.1%
who 28
 
3.7%
Other values (33) 210
27.7%
2023-12-09T22:08:56.960557image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
654
14.0%
t 519
11.1%
e 414
8.9%
o 396
8.5%
n 383
8.2%
r 379
8.1%
i 366
7.8%
s 362
7.8%
d 182
 
3.9%
y 122
 
2.6%
Other values (34) 892
19.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 3692
79.1%
Space Separator 654
 
14.0%
Uppercase Letter 293
 
6.3%
Decimal Number 28
 
0.6%
Other Punctuation 2
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 519
14.1%
e 414
11.2%
o 396
10.7%
n 383
10.4%
r 379
10.3%
i 366
9.9%
s 362
9.8%
d 182
 
4.9%
y 122
 
3.3%
a 121
 
3.3%
Other values (13) 448
12.1%
Uppercase Letter
ValueCountFrequency (%)
P 61
20.8%
C 48
16.4%
Y 48
16.4%
N 48
16.4%
O 40
13.7%
B 18
 
6.1%
Q 10
 
3.4%
S 5
 
1.7%
I 5
 
1.7%
G 4
 
1.4%
Other values (2) 6
 
2.0%
Decimal Number
ValueCountFrequency (%)
8 16
57.1%
1 6
 
21.4%
3 2
 
7.1%
4 1
 
3.6%
5 1
 
3.6%
6 1
 
3.6%
2 1
 
3.6%
Space Separator
ValueCountFrequency (%)
654
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 3985
85.4%
Common 684
 
14.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 519
13.0%
e 414
10.4%
o 396
9.9%
n 383
9.6%
r 379
9.5%
i 366
9.2%
s 362
9.1%
d 182
 
4.6%
y 122
 
3.1%
a 121
 
3.0%
Other values (25) 741
18.6%
Common
ValueCountFrequency (%)
654
95.6%
8 16
 
2.3%
1 6
 
0.9%
3 2
 
0.3%
, 2
 
0.3%
4 1
 
0.1%
5 1
 
0.1%
6 1
 
0.1%
2 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4669
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
654
14.0%
t 519
11.1%
e 414
8.9%
o 396
8.5%
n 383
8.2%
r 379
8.1%
i 366
7.8%
s 362
7.8%
d 182
 
3.9%
y 122
 
2.6%
Other values (34) 892
19.1%

admissionspriority13
Text

MISSING 

Distinct14
Distinct (%)23.0%
Missing379
Missing (%)86.1%
Memory size17.8 KiB
2023-12-09T22:08:57.210273image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length100
Median length76
Mean length40.3442623
Min length31

Characters and Unicode

Total characters2461
Distinct characters42
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)9.8%

Sample

1st rowPriority to students who apply and live in the zoned area
2nd rowOpen to New York City residents
3rd rowPriority to continuing 8th graders
4th rowOpen to New York City residents
5th rowPriority to Bronx students or residents
ValueCountFrequency (%)
to 61
14.5%
residents 50
11.9%
new 33
 
7.8%
york 33
 
7.8%
city 33
 
7.8%
open 30
 
7.1%
priority 30
 
7.1%
students 23
 
5.5%
or 17
 
4.0%
who 10
 
2.4%
Other values (32) 101
24.0%
2023-12-09T22:08:57.605662image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
360
14.6%
t 266
10.8%
e 242
9.8%
r 193
 
7.8%
o 191
 
7.8%
i 185
 
7.5%
n 182
 
7.4%
s 178
 
7.2%
d 98
 
4.0%
y 71
 
2.9%
Other values (32) 495
20.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1904
77.4%
Space Separator 360
 
14.6%
Uppercase Letter 182
 
7.4%
Decimal Number 13
 
0.5%
Other Punctuation 2
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 266
14.0%
e 242
12.7%
r 193
10.1%
o 191
10.0%
i 185
9.7%
n 182
9.6%
s 178
9.3%
d 98
 
5.1%
y 71
 
3.7%
a 53
 
2.8%
Other values (13) 245
12.9%
Uppercase Letter
ValueCountFrequency (%)
C 33
18.1%
Y 33
18.1%
N 33
18.1%
P 30
16.5%
O 30
16.5%
B 7
 
3.8%
I 5
 
2.7%
S 5
 
2.7%
Q 4
 
2.2%
D 1
 
0.5%
Decimal Number
ValueCountFrequency (%)
8 5
38.5%
1 4
30.8%
3 1
 
7.7%
4 1
 
7.7%
5 1
 
7.7%
6 1
 
7.7%
Space Separator
ValueCountFrequency (%)
360
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2086
84.8%
Common 375
 
15.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 266
12.8%
e 242
11.6%
r 193
9.3%
o 191
9.2%
i 185
8.9%
n 182
8.7%
s 178
8.5%
d 98
 
4.7%
y 71
 
3.4%
a 53
 
2.5%
Other values (24) 427
20.5%
Common
ValueCountFrequency (%)
360
96.0%
8 5
 
1.3%
1 4
 
1.1%
, 2
 
0.5%
3 1
 
0.3%
4 1
 
0.3%
5 1
 
0.3%
6 1
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2461
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
360
14.6%
t 266
10.8%
e 242
9.8%
r 193
 
7.8%
o 191
 
7.8%
i 185
 
7.5%
n 182
 
7.4%
s 178
 
7.2%
d 98
 
4.0%
y 71
 
2.9%
Other values (32) 495
20.1%

admissionspriority14
Text

MISSING 

Distinct12
Distinct (%)26.1%
Missing394
Missing (%)89.5%
Memory size16.9 KiB
2023-12-09T22:08:57.842302image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length76
Median length73
Mean length41.56521739
Min length31

Characters and Unicode

Total characters1912
Distinct characters42
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)8.7%

Sample

1st rowOpen to New York City residents
2nd rowPriority to continuing 8th graders
3rd rowOpen to New York City residents
4th rowPriority to Bronx students or residents who attend an information session
5th rowOpen to New York City residents
ValueCountFrequency (%)
to 46
14.1%
residents 36
 
11.0%
priority 24
 
7.3%
new 22
 
6.7%
york 22
 
6.7%
city 22
 
6.7%
open 20
 
6.1%
students 19
 
5.8%
or 14
 
4.3%
who 9
 
2.8%
Other values (26) 93
28.4%
2023-12-09T22:08:58.214653image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
281
14.7%
t 205
10.7%
e 182
9.5%
r 150
 
7.8%
o 149
 
7.8%
n 145
 
7.6%
i 140
 
7.3%
s 136
 
7.1%
d 81
 
4.2%
y 55
 
2.9%
Other values (32) 388
20.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1486
77.7%
Space Separator 281
 
14.7%
Uppercase Letter 130
 
6.8%
Decimal Number 13
 
0.7%
Other Punctuation 2
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 205
13.8%
e 182
12.2%
r 150
10.1%
o 149
10.0%
n 145
9.8%
i 140
9.4%
s 136
9.2%
d 81
 
5.5%
y 55
 
3.7%
a 50
 
3.4%
Other values (13) 193
13.0%
Uppercase Letter
ValueCountFrequency (%)
P 24
18.5%
C 22
16.9%
N 22
16.9%
Y 22
16.9%
O 20
15.4%
B 6
 
4.6%
I 4
 
3.1%
S 4
 
3.1%
Q 3
 
2.3%
G 2
 
1.5%
Decimal Number
ValueCountFrequency (%)
8 5
38.5%
1 4
30.8%
3 1
 
7.7%
4 1
 
7.7%
5 1
 
7.7%
6 1
 
7.7%
Space Separator
ValueCountFrequency (%)
281
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1616
84.5%
Common 296
 
15.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 205
12.7%
e 182
11.3%
r 150
9.3%
o 149
9.2%
n 145
9.0%
i 140
8.7%
s 136
8.4%
d 81
 
5.0%
y 55
 
3.4%
a 50
 
3.1%
Other values (24) 323
20.0%
Common
ValueCountFrequency (%)
281
94.9%
8 5
 
1.7%
1 4
 
1.4%
, 2
 
0.7%
3 1
 
0.3%
4 1
 
0.3%
5 1
 
0.3%
6 1
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1912
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
281
14.7%
t 205
10.7%
e 182
9.5%
r 150
 
7.8%
o 149
 
7.8%
n 145
 
7.6%
i 140
 
7.3%
s 136
 
7.1%
d 81
 
4.2%
y 55
 
2.9%
Other values (32) 388
20.3%

admissionspriority15
Text

MISSING 

Distinct10
Distinct (%)29.4%
Missing406
Missing (%)92.3%
Memory size16.1 KiB
2023-12-09T22:08:58.458660image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length83
Median length69
Mean length41.64705882
Min length31

Characters and Unicode

Total characters1416
Distinct characters38
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)11.8%

Sample

1st rowOpen to New York City residents
2nd rowPriority to Bronx students or residents
3rd rowOpen to New York City residents
4th rowOpen to New York City residents
5th rowGuaranteed offer to students who apply and live in the zoned area
ValueCountFrequency (%)
to 34
13.9%
residents 25
 
10.2%
new 16
 
6.5%
york 16
 
6.5%
city 16
 
6.5%
open 15
 
6.1%
priority 15
 
6.1%
students 15
 
6.1%
or 9
 
3.7%
who 7
 
2.9%
Other values (30) 77
31.4%
2023-12-09T22:08:58.834574image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
211
14.9%
t 146
10.3%
e 144
10.2%
r 106
 
7.5%
o 105
 
7.4%
n 104
 
7.3%
i 93
 
6.6%
s 93
 
6.6%
d 63
 
4.4%
a 47
 
3.3%
Other values (28) 304
21.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1104
78.0%
Space Separator 211
 
14.9%
Uppercase Letter 98
 
6.9%
Decimal Number 3
 
0.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 146
13.2%
e 144
13.0%
r 106
9.6%
o 105
9.5%
n 104
9.4%
i 93
8.4%
s 93
8.4%
d 63
 
5.7%
a 47
 
4.3%
y 37
 
3.4%
Other values (14) 166
15.0%
Uppercase Letter
ValueCountFrequency (%)
C 16
16.3%
Y 16
16.3%
N 16
16.3%
O 15
15.3%
P 15
15.3%
S 5
 
5.1%
B 4
 
4.1%
I 4
 
4.1%
G 4
 
4.1%
Q 1
 
1.0%
Other values (2) 2
 
2.0%
Space Separator
ValueCountFrequency (%)
211
100.0%
Decimal Number
ValueCountFrequency (%)
8 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1202
84.9%
Common 214
 
15.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 146
12.1%
e 144
12.0%
r 106
8.8%
o 105
 
8.7%
n 104
 
8.7%
i 93
 
7.7%
s 93
 
7.7%
d 63
 
5.2%
a 47
 
3.9%
y 37
 
3.1%
Other values (26) 264
22.0%
Common
ValueCountFrequency (%)
211
98.6%
8 3
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1416
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
211
14.9%
t 146
10.3%
e 144
10.2%
r 106
 
7.5%
o 105
 
7.4%
n 104
 
7.3%
i 93
 
6.6%
s 93
 
6.6%
d 63
 
4.4%
a 47
 
3.3%
Other values (28) 304
21.5%

admissionspriority16
Text

MISSING 

Distinct8
Distinct (%)36.4%
Missing418
Missing (%)95.0%
Memory size15.4 KiB
2023-12-09T22:08:59.079137image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length75
Median length69
Mean length46.36363636
Min length31

Characters and Unicode

Total characters1020
Distinct characters36
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)22.7%

Sample

1st rowOpen to New York City residents
2nd rowPriority to Bronx students or residents
3rd rowOpen to New York City residents
4th rowOpen to New York City residents
5th rowGuaranteed offer to students who apply and live in the zoned area
ValueCountFrequency (%)
to 22
 
12.5%
residents 16
 
9.1%
students 11
 
6.2%
new 10
 
5.7%
york 10
 
5.7%
city 10
 
5.7%
priority 9
 
5.1%
open 8
 
4.5%
who 7
 
4.0%
or 6
 
3.4%
Other values (25) 67
38.1%
2023-12-09T22:08:59.445138image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
154
15.1%
e 108
10.6%
t 102
10.0%
n 77
 
7.5%
r 73
 
7.2%
o 71
 
7.0%
s 64
 
6.3%
i 61
 
6.0%
d 48
 
4.7%
a 46
 
4.5%
Other values (26) 216
21.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 800
78.4%
Space Separator 154
 
15.1%
Uppercase Letter 65
 
6.4%
Decimal Number 1
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 108
13.5%
t 102
12.8%
n 77
9.6%
r 73
9.1%
o 71
8.9%
s 64
8.0%
i 61
7.6%
d 48
 
6.0%
a 46
 
5.8%
y 25
 
3.1%
Other values (13) 125
15.6%
Uppercase Letter
ValueCountFrequency (%)
C 10
15.4%
Y 10
15.4%
N 10
15.4%
P 9
13.8%
O 8
12.3%
G 5
7.7%
S 4
 
6.2%
I 4
 
6.2%
L 2
 
3.1%
B 2
 
3.1%
Space Separator
ValueCountFrequency (%)
154
100.0%
Decimal Number
ValueCountFrequency (%)
8 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 865
84.8%
Common 155
 
15.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 108
12.5%
t 102
11.8%
n 77
8.9%
r 73
 
8.4%
o 71
 
8.2%
s 64
 
7.4%
i 61
 
7.1%
d 48
 
5.5%
a 46
 
5.3%
y 25
 
2.9%
Other values (24) 190
22.0%
Common
ValueCountFrequency (%)
154
99.4%
8 1
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1020
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
154
15.1%
e 108
10.6%
t 102
10.0%
n 77
 
7.5%
r 73
 
7.2%
o 71
 
7.0%
s 64
 
6.3%
i 61
 
6.0%
d 48
 
4.7%
a 46
 
4.5%
Other values (26) 216
21.2%

admissionspriority17
Text

MISSING 

Distinct5
Distinct (%)38.5%
Missing427
Missing (%)97.0%
Memory size14.8 KiB
2023-12-09T22:08:59.699006image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length85
Median length69
Mean length50.84615385
Min length31

Characters and Unicode

Total characters661
Distinct characters34
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)15.4%

Sample

1st rowGuaranteed offer to students who apply and live in the zoned area
2nd rowOpen to New York City residents
3rd rowOpen to New York City residents
4th rowOpen to New York City residents
5th rowPriority to students whose have been in a Dual Language Spanish middle school program
ValueCountFrequency (%)
to 13
 
11.5%
residents 9
 
8.0%
students 8
 
7.1%
priority 6
 
5.3%
new 5
 
4.4%
city 5
 
4.4%
york 5
 
4.4%
who 4
 
3.5%
in 4
 
3.5%
open 4
 
3.5%
Other values (25) 50
44.2%
2023-12-09T22:09:00.064450image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
100
15.1%
e 68
10.3%
t 66
10.0%
n 50
 
7.6%
o 45
 
6.8%
s 44
 
6.7%
r 42
 
6.4%
i 38
 
5.7%
a 36
 
5.4%
d 33
 
5.0%
Other values (24) 139
21.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 522
79.0%
Space Separator 100
 
15.1%
Uppercase Letter 39
 
5.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 68
13.0%
t 66
12.6%
n 50
9.6%
o 45
8.6%
s 44
8.4%
r 42
8.0%
i 38
7.3%
a 36
6.9%
d 33
 
6.3%
y 14
 
2.7%
Other values (13) 86
16.5%
Uppercase Letter
ValueCountFrequency (%)
P 6
15.4%
N 5
12.8%
Y 5
12.8%
C 5
12.8%
S 5
12.8%
O 4
10.3%
I 4
10.3%
G 3
7.7%
D 1
 
2.6%
L 1
 
2.6%
Space Separator
ValueCountFrequency (%)
100
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 561
84.9%
Common 100
 
15.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 68
12.1%
t 66
11.8%
n 50
 
8.9%
o 45
 
8.0%
s 44
 
7.8%
r 42
 
7.5%
i 38
 
6.8%
a 36
 
6.4%
d 33
 
5.9%
y 14
 
2.5%
Other values (23) 125
22.3%
Common
ValueCountFrequency (%)
100
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 661
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
100
15.1%
e 68
10.3%
t 66
10.0%
n 50
 
7.6%
o 45
 
6.8%
s 44
 
6.7%
r 42
 
6.4%
i 38
 
5.7%
a 36
 
5.4%
d 33
 
5.0%
Other values (24) 139
21.0%

admissionspriority18
Text

MISSING 

Distinct2
Distinct (%)28.6%
Missing433
Missing (%)98.4%
Memory size14.5 KiB
2023-12-09T22:09:00.286663image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length65
Median length65
Mean length59.85714286
Min length47

Characters and Unicode

Total characters419
Distinct characters23
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowGuaranteed offer to students who apply and live in the zoned area
2nd rowGuaranteed offer to students who apply and live in the zoned area
3rd rowGuaranteed offer to students who apply and live in the zoned area
4th rowPriority to Staten Island students or residents
5th rowGuaranteed offer to students who apply and live in the zoned area
ValueCountFrequency (%)
to 7
 
9.5%
students 7
 
9.5%
guaranteed 5
 
6.8%
offer 5
 
6.8%
area 5
 
6.8%
zoned 5
 
6.8%
the 5
 
6.8%
in 5
 
6.8%
live 5
 
6.8%
and 5
 
6.8%
Other values (7) 20
27.0%
2023-12-09T22:09:00.646792image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
67
16.0%
e 48
11.5%
t 39
9.3%
a 34
 
8.1%
n 33
 
7.9%
o 26
 
6.2%
d 26
 
6.2%
r 23
 
5.5%
s 20
 
4.8%
i 16
 
3.8%
Other values (13) 87
20.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 341
81.4%
Space Separator 67
 
16.0%
Uppercase Letter 11
 
2.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 48
14.1%
t 39
11.4%
a 34
10.0%
n 33
9.7%
o 26
7.6%
d 26
7.6%
r 23
 
6.7%
s 20
 
5.9%
i 16
 
4.7%
u 12
 
3.5%
Other values (8) 64
18.8%
Uppercase Letter
ValueCountFrequency (%)
G 5
45.5%
P 2
 
18.2%
S 2
 
18.2%
I 2
 
18.2%
Space Separator
ValueCountFrequency (%)
67
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 352
84.0%
Common 67
 
16.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 48
13.6%
t 39
11.1%
a 34
9.7%
n 33
9.4%
o 26
 
7.4%
d 26
 
7.4%
r 23
 
6.5%
s 20
 
5.7%
i 16
 
4.5%
u 12
 
3.4%
Other values (12) 75
21.3%
Common
ValueCountFrequency (%)
67
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 419
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
67
16.0%
e 48
11.5%
t 39
9.3%
a 34
 
8.1%
n 33
 
7.9%
o 26
 
6.2%
d 26
 
6.2%
r 23
 
5.5%
s 20
 
4.8%
i 16
 
3.8%
Other values (13) 87
20.8%

admissionspriority19
Text

MISSING 

Distinct2
Distinct (%)100.0%
Missing438
Missing (%)99.5%
Memory size14.0 KiB
2023-12-09T22:09:00.883700image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length65
Median length56
Mean length56
Min length47

Characters and Unicode

Total characters112
Distinct characters23
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st rowPriority to Staten Island students or residents
2nd rowGuaranteed offer to students who apply and live in the zoned area
ValueCountFrequency (%)
students 2
 
10.5%
to 2
 
10.5%
priority 1
 
5.3%
apply 1
 
5.3%
zoned 1
 
5.3%
the 1
 
5.3%
in 1
 
5.3%
live 1
 
5.3%
and 1
 
5.3%
offer 1
 
5.3%
Other values (7) 7
36.8%
2023-12-09T22:09:01.232542image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
17
15.2%
e 12
10.7%
t 12
10.7%
n 9
8.0%
a 8
 
7.1%
o 7
 
6.2%
d 7
 
6.2%
r 7
 
6.2%
s 7
 
6.2%
i 5
 
4.5%
Other values (13) 21
18.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 91
81.2%
Space Separator 17
 
15.2%
Uppercase Letter 4
 
3.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 12
13.2%
t 12
13.2%
n 9
9.9%
a 8
8.8%
o 7
7.7%
d 7
7.7%
r 7
7.7%
s 7
7.7%
i 5
 
5.5%
l 3
 
3.3%
Other values (8) 14
15.4%
Uppercase Letter
ValueCountFrequency (%)
P 1
25.0%
I 1
25.0%
G 1
25.0%
S 1
25.0%
Space Separator
ValueCountFrequency (%)
17
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 95
84.8%
Common 17
 
15.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 12
12.6%
t 12
12.6%
n 9
9.5%
a 8
8.4%
o 7
 
7.4%
d 7
 
7.4%
r 7
 
7.4%
s 7
 
7.4%
i 5
 
5.3%
l 3
 
3.2%
Other values (12) 18
18.9%
Common
ValueCountFrequency (%)
17
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 112
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
17
15.2%
e 12
10.7%
t 12
10.7%
n 9
8.0%
a 8
 
7.1%
o 7
 
6.2%
d 7
 
6.2%
r 7
 
6.2%
s 7
 
6.2%
i 5
 
4.5%
Other values (13) 21
18.8%

admissionspriority110
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing439
Missing (%)99.8%
Memory size14.0 KiB
2023-12-09T22:09:01.432274image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length65
Median length65
Mean length65
Min length65

Characters and Unicode

Total characters65
Distinct characters20
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowGuaranteed offer to students who apply and live in the zoned area
ValueCountFrequency (%)
guaranteed 1
8.3%
offer 1
8.3%
to 1
8.3%
students 1
8.3%
who 1
8.3%
apply 1
8.3%
and 1
8.3%
live 1
8.3%
in 1
8.3%
the 1
8.3%
Other values (2) 2
16.7%
2023-12-09T22:09:01.764132image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
11
16.9%
e 8
12.3%
a 6
 
9.2%
n 5
 
7.7%
t 5
 
7.7%
d 4
 
6.2%
o 4
 
6.2%
r 3
 
4.6%
f 2
 
3.1%
i 2
 
3.1%
Other values (10) 15
23.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 53
81.5%
Space Separator 11
 
16.9%
Uppercase Letter 1
 
1.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 8
15.1%
a 6
11.3%
n 5
9.4%
t 5
9.4%
d 4
 
7.5%
o 4
 
7.5%
r 3
 
5.7%
f 2
 
3.8%
i 2
 
3.8%
u 2
 
3.8%
Other values (8) 12
22.6%
Space Separator
ValueCountFrequency (%)
11
100.0%
Uppercase Letter
ValueCountFrequency (%)
G 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 54
83.1%
Common 11
 
16.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 8
14.8%
a 6
11.1%
n 5
 
9.3%
t 5
 
9.3%
d 4
 
7.4%
o 4
 
7.4%
r 3
 
5.6%
f 2
 
3.7%
i 2
 
3.7%
u 2
 
3.7%
Other values (9) 13
24.1%
Common
ValueCountFrequency (%)
11
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 65
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
11
16.9%
e 8
12.3%
a 6
 
9.2%
n 5
 
7.7%
t 5
 
7.7%
d 4
 
6.2%
o 4
 
6.2%
r 3
 
4.6%
f 2
 
3.1%
i 2
 
3.1%
Other values (10) 15
23.1%

admissionspriority21
Text

MISSING 

Distinct30
Distinct (%)9.2%
Missing114
Missing (%)25.9%
Memory size37.7 KiB
2023-12-09T22:09:01.992783image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length125
Median length93
Mean length49.87116564
Min length31

Characters and Unicode

Total characters16258
Distinct characters47
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique18 ?
Unique (%)5.5%

Sample

1st rowThen to Manhattan students or residents
2nd rowThen to New York City residents
3rd rowThen to New York City residents
4th rowThen to New York City residents who attend an information session
5th rowThen to New York City residents who attend an information session
ValueCountFrequency (%)
to 326
11.6%
then 325
11.6%
residents 325
11.6%
new 244
8.7%
york 244
8.7%
city 244
8.7%
who 159
 
5.7%
session 157
 
5.6%
information 157
 
5.6%
an 157
 
5.6%
Other values (55) 471
16.8%
2023-12-09T22:09:02.362410image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2483
15.3%
e 1658
10.2%
n 1622
10.0%
t 1609
9.9%
o 1342
8.3%
s 1324
8.1%
i 1091
 
6.7%
r 873
 
5.4%
d 575
 
3.5%
a 550
 
3.4%
Other values (37) 3131
19.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 12573
77.3%
Space Separator 2483
 
15.3%
Uppercase Letter 1147
 
7.1%
Decimal Number 49
 
0.3%
Other Punctuation 6
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 1658
13.2%
n 1622
12.9%
t 1609
12.8%
o 1342
10.7%
s 1324
10.5%
i 1091
8.7%
r 873
6.9%
d 575
 
4.6%
a 550
 
4.4%
h 510
 
4.1%
Other values (12) 1419
11.3%
Uppercase Letter
ValueCountFrequency (%)
T 325
28.3%
Y 244
21.3%
N 244
21.3%
C 244
21.3%
B 37
 
3.2%
M 18
 
1.6%
D 17
 
1.5%
Q 10
 
0.9%
S 3
 
0.3%
A 2
 
0.2%
Other values (3) 3
 
0.3%
Decimal Number
ValueCountFrequency (%)
1 10
20.4%
2 9
18.4%
3 8
16.3%
5 6
12.2%
4 5
10.2%
6 4
 
8.2%
9 3
 
6.1%
0 2
 
4.1%
7 1
 
2.0%
8 1
 
2.0%
Space Separator
ValueCountFrequency (%)
2483
100.0%
Other Punctuation
ValueCountFrequency (%)
, 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 13720
84.4%
Common 2538
 
15.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 1658
12.1%
n 1622
11.8%
t 1609
11.7%
o 1342
9.8%
s 1324
9.7%
i 1091
8.0%
r 873
 
6.4%
d 575
 
4.2%
a 550
 
4.0%
h 510
 
3.7%
Other values (25) 2566
18.7%
Common
ValueCountFrequency (%)
2483
97.8%
1 10
 
0.4%
2 9
 
0.4%
3 8
 
0.3%
, 6
 
0.2%
5 6
 
0.2%
4 5
 
0.2%
6 4
 
0.2%
9 3
 
0.1%
0 2
 
0.1%
Other values (2) 2
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 16258
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2483
15.3%
e 1658
10.2%
n 1622
10.0%
t 1609
9.9%
o 1342
8.3%
s 1324
8.1%
i 1091
 
6.7%
r 873
 
5.4%
d 575
 
3.5%
a 550
 
3.4%
Other values (37) 3131
19.3%

admissionspriority22
Text

MISSING 

Distinct11
Distinct (%)18.0%
Missing379
Missing (%)86.1%
Memory size17.9 KiB
2023-12-09T22:09:02.581084image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length72
Median length31
Mean length42.7704918
Min length31

Characters and Unicode

Total characters2609
Distinct characters33
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7 ?
Unique (%)11.5%

Sample

1st rowThen to New York City residents
2nd rowThen to New York City residents who attend an information session
3rd rowThen to New York City residents
4th rowThen to New York City residents
5th rowThen to New York City residents
ValueCountFrequency (%)
then 61
13.1%
to 61
13.1%
residents 61
13.1%
new 49
10.5%
york 49
10.5%
city 49
10.5%
who 18
 
3.9%
attend 18
 
3.9%
an 18
 
3.9%
information 18
 
3.9%
Other values (15) 64
13.7%
2023-12-09T22:09:02.929222image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
405
15.5%
e 282
10.8%
t 257
9.9%
n 234
9.0%
s 207
 
7.9%
o 206
 
7.9%
i 172
 
6.6%
r 151
 
5.8%
d 93
 
3.6%
h 79
 
3.0%
Other values (23) 523
20.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1972
75.6%
Space Separator 405
 
15.5%
Uppercase Letter 220
 
8.4%
Decimal Number 10
 
0.4%
Other Punctuation 2
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 282
14.3%
t 257
13.0%
n 234
11.9%
s 207
10.5%
o 206
10.4%
i 172
8.7%
r 151
7.7%
d 93
 
4.7%
h 79
 
4.0%
w 67
 
3.4%
Other values (9) 224
11.4%
Uppercase Letter
ValueCountFrequency (%)
T 61
27.7%
C 49
22.3%
Y 49
22.3%
N 49
22.3%
B 7
 
3.2%
D 4
 
1.8%
Q 1
 
0.5%
Decimal Number
ValueCountFrequency (%)
3 3
30.0%
5 3
30.0%
1 2
20.0%
4 1
 
10.0%
6 1
 
10.0%
Space Separator
ValueCountFrequency (%)
405
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2192
84.0%
Common 417
 
16.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 282
12.9%
t 257
11.7%
n 234
10.7%
s 207
9.4%
o 206
9.4%
i 172
 
7.8%
r 151
 
6.9%
d 93
 
4.2%
h 79
 
3.6%
w 67
 
3.1%
Other values (16) 444
20.3%
Common
ValueCountFrequency (%)
405
97.1%
3 3
 
0.7%
5 3
 
0.7%
1 2
 
0.5%
, 2
 
0.5%
4 1
 
0.2%
6 1
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2609
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
405
15.5%
e 282
10.8%
t 257
9.9%
n 234
9.0%
s 207
 
7.9%
o 206
 
7.9%
i 172
 
6.6%
r 151
 
5.8%
d 93
 
3.6%
h 79
 
3.0%
Other values (23) 523
20.0%

admissionspriority23
Text

MISSING 

Distinct7
Distinct (%)25.0%
Missing412
Missing (%)93.6%
Memory size15.5 KiB
2023-12-09T22:09:03.145888image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length72
Median length31
Mean length35.35714286
Min length31

Characters and Unicode

Total characters990
Distinct characters31
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)17.9%

Sample

1st rowThen to New York City residents
2nd rowThen to New York City residents
3rd rowThen to New York City residents
4th rowThen to New York City residents
5th rowThen to New York City residents
ValueCountFrequency (%)
then 28
15.3%
residents 28
15.3%
to 28
15.3%
new 22
12.0%
york 22
12.0%
city 22
12.0%
students 6
 
3.3%
or 6
 
3.3%
brooklyn 3
 
1.6%
an 2
 
1.1%
Other values (12) 16
8.7%
2023-12-09T22:09:03.479434image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
155
15.7%
e 116
11.7%
t 100
10.1%
s 77
 
7.8%
n 77
 
7.8%
o 71
 
7.2%
r 64
 
6.5%
i 60
 
6.1%
d 37
 
3.7%
h 30
 
3.0%
Other values (21) 203
20.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 729
73.6%
Space Separator 155
 
15.7%
Uppercase Letter 100
 
10.1%
Decimal Number 5
 
0.5%
Other Punctuation 1
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 116
15.9%
t 100
13.7%
s 77
10.6%
n 77
10.6%
o 71
9.7%
r 64
8.8%
i 60
8.2%
d 37
 
5.1%
h 30
 
4.1%
k 25
 
3.4%
Other values (9) 72
9.9%
Uppercase Letter
ValueCountFrequency (%)
T 28
28.0%
Y 22
22.0%
N 22
22.0%
C 22
22.0%
B 4
 
4.0%
D 2
 
2.0%
Decimal Number
ValueCountFrequency (%)
3 2
40.0%
1 1
20.0%
5 1
20.0%
6 1
20.0%
Space Separator
ValueCountFrequency (%)
155
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 829
83.7%
Common 161
 
16.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 116
14.0%
t 100
12.1%
s 77
9.3%
n 77
9.3%
o 71
8.6%
r 64
 
7.7%
i 60
 
7.2%
d 37
 
4.5%
h 30
 
3.6%
T 28
 
3.4%
Other values (15) 169
20.4%
Common
ValueCountFrequency (%)
155
96.3%
3 2
 
1.2%
1 1
 
0.6%
, 1
 
0.6%
5 1
 
0.6%
6 1
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 990
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
155
15.7%
e 116
11.7%
t 100
10.1%
s 77
 
7.8%
n 77
 
7.8%
o 71
 
7.2%
r 64
 
6.5%
i 60
 
6.1%
d 37
 
3.7%
h 30
 
3.0%
Other values (21) 203
20.5%

admissionspriority24
Text

MISSING 

Distinct7
Distinct (%)33.3%
Missing419
Missing (%)95.2%
Memory size15.2 KiB
2023-12-09T22:09:03.700587image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length75
Median length31
Mean length38.23809524
Min length31

Characters and Unicode

Total characters803
Distinct characters32
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)23.8%

Sample

1st rowThen to New York City residents
2nd rowThen to New York City residents who attend an information session
3rd rowThen to New York City residents
4th rowThen to New York City residents
5th rowThen to New York City residents
ValueCountFrequency (%)
then 21
14.3%
residents 21
14.3%
to 21
14.3%
new 16
10.9%
york 16
10.9%
city 16
10.9%
students 5
 
3.4%
or 5
 
3.4%
who 3
 
2.0%
attend 3
 
2.0%
Other values (13) 20
13.6%
2023-12-09T22:09:04.051562image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
126
15.7%
e 90
11.2%
t 83
10.3%
n 65
8.1%
s 65
8.1%
o 57
 
7.1%
i 52
 
6.5%
r 50
 
6.2%
d 30
 
3.7%
h 24
 
3.0%
Other values (22) 161
20.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 595
74.1%
Space Separator 126
 
15.7%
Uppercase Letter 74
 
9.2%
Decimal Number 7
 
0.9%
Other Punctuation 1
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 90
15.1%
t 83
13.9%
n 65
10.9%
s 65
10.9%
o 57
9.6%
i 52
8.7%
r 50
8.4%
d 30
 
5.0%
h 24
 
4.0%
w 19
 
3.2%
Other values (9) 60
10.1%
Uppercase Letter
ValueCountFrequency (%)
T 21
28.4%
Y 16
21.6%
N 16
21.6%
C 16
21.6%
D 3
 
4.1%
B 2
 
2.7%
Decimal Number
ValueCountFrequency (%)
1 2
28.6%
3 2
28.6%
4 1
14.3%
5 1
14.3%
6 1
14.3%
Space Separator
ValueCountFrequency (%)
126
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 669
83.3%
Common 134
 
16.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 90
13.5%
t 83
12.4%
n 65
9.7%
s 65
9.7%
o 57
8.5%
i 52
 
7.8%
r 50
 
7.5%
d 30
 
4.5%
h 24
 
3.6%
T 21
 
3.1%
Other values (15) 132
19.7%
Common
ValueCountFrequency (%)
126
94.0%
1 2
 
1.5%
3 2
 
1.5%
4 1
 
0.7%
, 1
 
0.7%
5 1
 
0.7%
6 1
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 803
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
126
15.7%
e 90
11.2%
t 83
10.3%
n 65
8.1%
s 65
8.1%
o 57
 
7.1%
i 52
 
6.5%
r 50
 
6.2%
d 30
 
3.7%
h 24
 
3.0%
Other values (22) 161
20.0%

admissionspriority25
Text

MISSING 

Distinct6
Distinct (%)40.0%
Missing425
Missing (%)96.6%
Memory size14.8 KiB
2023-12-09T22:09:04.275070image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length98
Median length31
Mean length38.13333333
Min length31

Characters and Unicode

Total characters572
Distinct characters36
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)33.3%

Sample

1st rowThen to New York City residents
2nd rowThen to Brooklyn students or residents
3rd rowThen to New York City residents
4th rowThen to New York City residents
5th rowThen to Districts 3, 5 and 6 students or residents
ValueCountFrequency (%)
then 15
14.4%
to 15
14.4%
residents 14
13.5%
new 10
9.6%
york 10
9.6%
city 10
9.6%
students 5
 
4.8%
or 4
 
3.8%
5 1
 
1.0%
education 1
 
1.0%
Other values (19) 19
18.3%
2023-12-09T22:09:04.635805image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
89
15.6%
e 62
10.8%
t 55
9.6%
n 44
 
7.7%
s 44
 
7.7%
o 38
 
6.6%
i 36
 
6.3%
r 35
 
6.1%
d 23
 
4.0%
h 19
 
3.3%
Other values (26) 127
22.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 424
74.1%
Space Separator 89
 
15.6%
Uppercase Letter 53
 
9.3%
Decimal Number 5
 
0.9%
Other Punctuation 1
 
0.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 62
14.6%
t 55
13.0%
n 44
10.4%
s 44
10.4%
o 38
9.0%
i 36
8.5%
r 35
8.3%
d 23
 
5.4%
h 19
 
4.5%
k 11
 
2.6%
Other values (12) 57
13.4%
Uppercase Letter
ValueCountFrequency (%)
T 16
30.2%
C 10
18.9%
Y 10
18.9%
N 10
18.9%
B 3
 
5.7%
D 2
 
3.8%
E 1
 
1.9%
S 1
 
1.9%
Decimal Number
ValueCountFrequency (%)
3 2
40.0%
1 1
20.0%
5 1
20.0%
6 1
20.0%
Space Separator
ValueCountFrequency (%)
89
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 477
83.4%
Common 95
 
16.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 62
13.0%
t 55
11.5%
n 44
9.2%
s 44
9.2%
o 38
 
8.0%
i 36
 
7.5%
r 35
 
7.3%
d 23
 
4.8%
h 19
 
4.0%
T 16
 
3.4%
Other values (20) 105
22.0%
Common
ValueCountFrequency (%)
89
93.7%
3 2
 
2.1%
1 1
 
1.1%
, 1
 
1.1%
5 1
 
1.1%
6 1
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 572
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
89
15.6%
e 62
10.8%
t 55
9.6%
n 44
 
7.7%
s 44
 
7.7%
o 38
 
6.6%
i 36
 
6.3%
r 35
 
6.1%
d 23
 
4.0%
h 19
 
3.3%
Other values (26) 127
22.2%

admissionspriority26
Text

MISSING 

Distinct2
Distinct (%)22.2%
Missing431
Missing (%)98.0%
Memory size14.4 KiB
2023-12-09T22:09:04.844867image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length84
Median length31
Mean length36.88888889
Min length31

Characters and Unicode

Total characters332
Distinct characters27
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)11.1%

Sample

1st rowThen to New York City residents
2nd rowThen to New York City residents
3rd rowThen to Districts 3, 5 and 6 students or residents who attend an information session
4th rowThen to New York City residents
5th rowThen to New York City residents
ValueCountFrequency (%)
then 9
14.3%
residents 9
14.3%
to 9
14.3%
new 8
12.7%
york 8
12.7%
city 8
12.7%
or 1
 
1.6%
information 1
 
1.6%
an 1
 
1.6%
attend 1
 
1.6%
Other values (8) 8
12.7%
2023-12-09T22:09:05.170043image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
54
16.3%
e 38
11.4%
t 33
9.9%
n 25
 
7.5%
s 25
 
7.5%
i 22
 
6.6%
o 22
 
6.6%
r 20
 
6.0%
d 12
 
3.6%
h 10
 
3.0%
Other values (17) 71
21.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 240
72.3%
Space Separator 54
 
16.3%
Uppercase Letter 34
 
10.2%
Decimal Number 3
 
0.9%
Other Punctuation 1
 
0.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 38
15.8%
t 33
13.8%
n 25
10.4%
s 25
10.4%
i 22
9.2%
o 22
9.2%
r 20
8.3%
d 12
 
5.0%
h 10
 
4.2%
w 9
 
3.8%
Other values (7) 24
10.0%
Uppercase Letter
ValueCountFrequency (%)
T 9
26.5%
C 8
23.5%
Y 8
23.5%
N 8
23.5%
D 1
 
2.9%
Decimal Number
ValueCountFrequency (%)
3 1
33.3%
5 1
33.3%
6 1
33.3%
Space Separator
ValueCountFrequency (%)
54
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 274
82.5%
Common 58
 
17.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 38
13.9%
t 33
12.0%
n 25
9.1%
s 25
9.1%
i 22
 
8.0%
o 22
 
8.0%
r 20
 
7.3%
d 12
 
4.4%
h 10
 
3.6%
T 9
 
3.3%
Other values (12) 58
21.2%
Common
ValueCountFrequency (%)
54
93.1%
3 1
 
1.7%
, 1
 
1.7%
5 1
 
1.7%
6 1
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 332
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
54
16.3%
e 38
11.4%
t 33
9.9%
n 25
 
7.5%
s 25
 
7.5%
i 22
 
6.6%
o 22
 
6.6%
r 20
 
6.0%
d 12
 
3.6%
h 10
 
3.0%
Other values (17) 71
21.4%

admissionspriority27
Text

MISSING 

Distinct2
Distinct (%)33.3%
Missing434
Missing (%)98.6%
Memory size14.3 KiB
2023-12-09T22:09:05.381733image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length98
Median length31
Mean length42.16666667
Min length31

Characters and Unicode

Total characters253
Distinct characters29
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)16.7%

Sample

1st rowThen to students who have been in a Transitional Bilingual Education Spanish middle school program
2nd rowThen to New York City residents
3rd rowThen to New York City residents
4th rowThen to New York City residents
5th rowThen to New York City residents
ValueCountFrequency (%)
then 6
13.3%
to 6
13.3%
new 5
11.1%
york 5
11.1%
city 5
11.1%
residents 5
11.1%
transitional 1
 
2.2%
school 1
 
2.2%
middle 1
 
2.2%
spanish 1
 
2.2%
Other values (9) 9
20.0%
2023-12-09T22:09:05.717452image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
39
15.4%
e 26
 
10.3%
t 20
 
7.9%
n 19
 
7.5%
i 18
 
7.1%
o 17
 
6.7%
s 15
 
5.9%
r 13
 
5.1%
h 10
 
4.0%
d 9
 
3.6%
Other values (19) 67
26.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 189
74.7%
Space Separator 39
 
15.4%
Uppercase Letter 25
 
9.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 26
13.8%
t 20
10.6%
n 19
10.1%
i 18
9.5%
o 17
9.0%
s 15
7.9%
r 13
 
6.9%
h 10
 
5.3%
d 9
 
4.8%
a 8
 
4.2%
Other values (11) 34
18.0%
Uppercase Letter
ValueCountFrequency (%)
T 7
28.0%
C 5
20.0%
Y 5
20.0%
N 5
20.0%
B 1
 
4.0%
E 1
 
4.0%
S 1
 
4.0%
Space Separator
ValueCountFrequency (%)
39
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 214
84.6%
Common 39
 
15.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 26
12.1%
t 20
 
9.3%
n 19
 
8.9%
i 18
 
8.4%
o 17
 
7.9%
s 15
 
7.0%
r 13
 
6.1%
h 10
 
4.7%
d 9
 
4.2%
a 8
 
3.7%
Other values (18) 59
27.6%
Common
ValueCountFrequency (%)
39
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 253
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
39
15.4%
e 26
 
10.3%
t 20
 
7.9%
n 19
 
7.5%
i 18
 
7.1%
o 17
 
6.7%
s 15
 
5.9%
r 13
 
5.1%
h 10
 
4.0%
d 9
 
3.6%
Other values (19) 67
26.5%

admissionspriority28
Text

MISSING 

Distinct2
Distinct (%)66.7%
Missing437
Missing (%)99.3%
Memory size14.0 KiB
2023-12-09T22:09:05.910039image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length31
Median length31
Mean length21.66666667
Min length3

Characters and Unicode

Total characters65
Distinct characters17
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)33.3%

Sample

1st rowThen to New York City residents
2nd rownts
3rd rowThen to New York City residents
ValueCountFrequency (%)
then 2
15.4%
to 2
15.4%
new 2
15.4%
york 2
15.4%
city 2
15.4%
residents 2
15.4%
nts 1
7.7%
2023-12-09T22:09:06.215301image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
10
15.4%
e 8
12.3%
t 7
10.8%
n 5
 
7.7%
s 5
 
7.7%
o 4
 
6.2%
i 4
 
6.2%
r 4
 
6.2%
T 2
 
3.1%
C 2
 
3.1%
Other values (7) 14
21.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 47
72.3%
Space Separator 10
 
15.4%
Uppercase Letter 8
 
12.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 8
17.0%
t 7
14.9%
n 5
10.6%
s 5
10.6%
o 4
8.5%
i 4
8.5%
r 4
8.5%
y 2
 
4.3%
w 2
 
4.3%
k 2
 
4.3%
Other values (2) 4
8.5%
Uppercase Letter
ValueCountFrequency (%)
T 2
25.0%
C 2
25.0%
Y 2
25.0%
N 2
25.0%
Space Separator
ValueCountFrequency (%)
10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 55
84.6%
Common 10
 
15.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 8
14.5%
t 7
12.7%
n 5
9.1%
s 5
9.1%
o 4
 
7.3%
i 4
 
7.3%
r 4
 
7.3%
T 2
 
3.6%
C 2
 
3.6%
y 2
 
3.6%
Other values (6) 12
21.8%
Common
ValueCountFrequency (%)
10
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 65
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
10
15.4%
e 8
12.3%
t 7
10.8%
n 5
 
7.7%
s 5
 
7.7%
o 4
 
6.2%
i 4
 
6.2%
r 4
 
6.2%
T 2
 
3.1%
C 2
 
3.1%
Other values (7) 14
21.5%

admissionspriority29
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing439
Missing (%)99.8%
Memory size13.9 KiB
2023-12-09T22:09:06.404406image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length31
Median length31
Mean length31
Min length31

Characters and Unicode

Total characters31
Distinct characters17
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowThen to New York City residents
ValueCountFrequency (%)
then 1
16.7%
to 1
16.7%
new 1
16.7%
york 1
16.7%
city 1
16.7%
residents 1
16.7%
2023-12-09T22:09:06.704987image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5
16.1%
e 4
12.9%
t 3
9.7%
n 2
 
6.5%
o 2
 
6.5%
s 2
 
6.5%
i 2
 
6.5%
r 2
 
6.5%
T 1
 
3.2%
C 1
 
3.2%
Other values (7) 7
22.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 22
71.0%
Space Separator 5
 
16.1%
Uppercase Letter 4
 
12.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 4
18.2%
t 3
13.6%
n 2
9.1%
o 2
9.1%
s 2
9.1%
i 2
9.1%
r 2
9.1%
y 1
 
4.5%
w 1
 
4.5%
k 1
 
4.5%
Other values (2) 2
9.1%
Uppercase Letter
ValueCountFrequency (%)
T 1
25.0%
C 1
25.0%
Y 1
25.0%
N 1
25.0%
Space Separator
ValueCountFrequency (%)
5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 26
83.9%
Common 5
 
16.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 4
15.4%
t 3
11.5%
n 2
 
7.7%
o 2
 
7.7%
s 2
 
7.7%
i 2
 
7.7%
r 2
 
7.7%
T 1
 
3.8%
C 1
 
3.8%
y 1
 
3.8%
Other values (6) 6
23.1%
Common
ValueCountFrequency (%)
5
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 31
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5
16.1%
e 4
12.9%
t 3
9.7%
n 2
 
6.5%
o 2
 
6.5%
s 2
 
6.5%
i 2
 
6.5%
r 2
 
6.5%
T 1
 
3.2%
C 1
 
3.2%
Other values (7) 7
22.6%

admissionspriority210
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing440
Missing (%)100.0%
Memory size3.6 KiB

admissionspriority31
Text

MISSING 

Distinct13
Distinct (%)6.3%
Missing234
Missing (%)53.2%
Memory size27.1 KiB
2023-12-09T22:09:06.947261image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length121
Median length70
Mean length40.52427184
Min length31

Characters and Unicode

Total characters8348
Distinct characters40
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7 ?
Unique (%)3.4%

Sample

1st rowThen to New York City residents
2nd rowThen to Queens students or residents
3rd rowThen to New York City residents
4th rowThen to Manhattan students or residents
5th rowThen to Queens students or residents
ValueCountFrequency (%)
then 206
14.4%
to 206
14.4%
residents 205
14.3%
students 126
8.8%
or 126
8.8%
new 80
 
5.6%
york 80
 
5.6%
city 80
 
5.6%
bronx 54
 
3.8%
who 34
 
2.4%
Other values (34) 234
16.4%
2023-12-09T22:09:07.324843image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1225
14.7%
e 945
11.3%
t 897
10.7%
n 854
10.2%
s 791
9.5%
o 661
7.9%
r 528
 
6.3%
i 392
 
4.7%
d 372
 
4.5%
h 266
 
3.2%
Other values (30) 1417
17.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 6528
78.2%
Space Separator 1225
 
14.7%
Uppercase Letter 587
 
7.0%
Decimal Number 6
 
0.1%
Other Punctuation 2
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 945
14.5%
t 897
13.7%
n 854
13.1%
s 791
12.1%
o 661
10.1%
r 528
8.1%
i 392
6.0%
d 372
 
5.7%
h 266
 
4.1%
a 173
 
2.7%
Other values (12) 649
9.9%
Uppercase Letter
ValueCountFrequency (%)
T 206
35.1%
B 81
 
13.8%
Y 80
 
13.6%
N 80
 
13.6%
C 79
 
13.5%
M 24
 
4.1%
Q 22
 
3.7%
I 6
 
1.0%
S 4
 
0.7%
H 3
 
0.5%
Other values (2) 2
 
0.3%
Decimal Number
ValueCountFrequency (%)
2 2
33.3%
1 2
33.3%
0 1
16.7%
3 1
16.7%
Space Separator
ValueCountFrequency (%)
1225
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 7115
85.2%
Common 1233
 
14.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 945
13.3%
t 897
12.6%
n 854
12.0%
s 791
11.1%
o 661
9.3%
r 528
7.4%
i 392
 
5.5%
d 372
 
5.2%
h 266
 
3.7%
T 206
 
2.9%
Other values (24) 1203
16.9%
Common
ValueCountFrequency (%)
1225
99.4%
2 2
 
0.2%
, 2
 
0.2%
1 2
 
0.2%
0 1
 
0.1%
3 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8348
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1225
14.7%
e 945
11.3%
t 897
10.7%
n 854
10.2%
s 791
9.5%
o 661
7.9%
r 528
 
6.3%
i 392
 
4.7%
d 372
 
4.5%
h 266
 
3.2%
Other values (30) 1417
17.0%

admissionspriority32
Text

MISSING 

Distinct7
Distinct (%)26.9%
Missing414
Missing (%)94.1%
Memory size15.5 KiB
2023-12-09T22:09:07.536342image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length65
Median length41
Mean length38.26923077
Min length31

Characters and Unicode

Total characters995
Distinct characters28
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)3.8%

Sample

1st rowThen to New York City residents
2nd rowThen to Queens students or residents
3rd rowThen to New York City residents who attend an information session
4th rowThen to Brooklyn students or residents
5th rowThen to Queens students or residents
ValueCountFrequency (%)
then 26
14.9%
to 26
14.9%
residents 25
14.4%
students 14
8.0%
or 13
7.5%
new 12
6.9%
york 12
6.9%
city 12
6.9%
bronx 4
 
2.3%
who 4
 
2.3%
Other values (12) 26
14.9%
2023-12-09T22:09:07.883687image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
148
14.9%
e 118
11.9%
t 105
10.6%
n 97
9.7%
s 90
9.0%
o 77
7.7%
r 62
 
6.2%
i 48
 
4.8%
d 43
 
4.3%
h 33
 
3.3%
Other values (18) 174
17.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 772
77.6%
Space Separator 148
 
14.9%
Uppercase Letter 75
 
7.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 118
15.3%
t 105
13.6%
n 97
12.6%
s 90
11.7%
o 77
10.0%
r 62
8.0%
i 48
6.2%
d 43
 
5.6%
h 33
 
4.3%
a 17
 
2.2%
Other values (10) 82
10.6%
Uppercase Letter
ValueCountFrequency (%)
T 26
34.7%
C 12
16.0%
Y 12
16.0%
N 12
16.0%
B 8
 
10.7%
Q 3
 
4.0%
M 2
 
2.7%
Space Separator
ValueCountFrequency (%)
148
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 847
85.1%
Common 148
 
14.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 118
13.9%
t 105
12.4%
n 97
11.5%
s 90
10.6%
o 77
9.1%
r 62
7.3%
i 48
 
5.7%
d 43
 
5.1%
h 33
 
3.9%
T 26
 
3.1%
Other values (17) 148
17.5%
Common
ValueCountFrequency (%)
148
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 995
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
148
14.9%
e 118
11.9%
t 105
10.6%
n 97
9.7%
s 90
9.0%
o 77
7.7%
r 62
 
6.2%
i 48
 
4.8%
d 43
 
4.3%
h 33
 
3.3%
Other values (18) 174
17.5%

admissionspriority33
Text

MISSING 

Distinct3
Distinct (%)50.0%
Missing434
Missing (%)98.6%
Memory size14.2 KiB
2023-12-09T22:09:08.082098image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length65
Median length31
Mean length37.83333333
Min length31

Characters and Unicode

Total characters227
Distinct characters23
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)33.3%

Sample

1st rowThen to New York City residents
2nd rowThen to New York City residents
3rd rowThen to Brooklyn students or residents
4th rowThen to New York City residents
5th rowThen to New York City residents
ValueCountFrequency (%)
then 6
14.6%
to 6
14.6%
residents 6
14.6%
new 5
12.2%
york 5
12.2%
city 5
12.2%
brooklyn 1
 
2.4%
students 1
 
2.4%
or 1
 
2.4%
who 1
 
2.4%
Other values (4) 4
9.8%
2023-12-09T22:09:08.413677image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
35
15.4%
e 26
11.5%
t 22
9.7%
n 19
8.4%
o 18
 
7.9%
s 17
 
7.5%
i 14
 
6.2%
r 14
 
6.2%
d 8
 
3.5%
h 7
 
3.1%
Other values (13) 47
20.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 170
74.9%
Space Separator 35
 
15.4%
Uppercase Letter 22
 
9.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 26
15.3%
t 22
12.9%
n 19
11.2%
o 18
10.6%
s 17
10.0%
i 14
8.2%
r 14
8.2%
d 8
 
4.7%
h 7
 
4.1%
y 6
 
3.5%
Other values (7) 19
11.2%
Uppercase Letter
ValueCountFrequency (%)
T 6
27.3%
C 5
22.7%
Y 5
22.7%
N 5
22.7%
B 1
 
4.5%
Space Separator
ValueCountFrequency (%)
35
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 192
84.6%
Common 35
 
15.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 26
13.5%
t 22
11.5%
n 19
9.9%
o 18
9.4%
s 17
8.9%
i 14
 
7.3%
r 14
 
7.3%
d 8
 
4.2%
h 7
 
3.6%
T 6
 
3.1%
Other values (12) 41
21.4%
Common
ValueCountFrequency (%)
35
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 227
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
35
15.4%
e 26
11.5%
t 22
9.7%
n 19
8.4%
o 18
 
7.9%
s 17
 
7.5%
i 14
 
6.2%
r 14
 
6.2%
d 8
 
3.5%
h 7
 
3.1%
Other values (13) 47
20.7%

admissionspriority34
Text

MISSING 

Distinct4
Distinct (%)57.1%
Missing433
Missing (%)98.4%
Memory size14.3 KiB
2023-12-09T22:09:08.619301image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length72
Median length31
Mean length38.42857143
Min length31

Characters and Unicode

Total characters269
Distinct characters24
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)42.9%

Sample

1st rowThen to Bronx students or residents
2nd rowThen to New York City residents
3rd rowThen to New York City residents
4th rowThen to Brooklyn students or residents who attend an information session
5th rowThen to Brooklyn students or residents
ValueCountFrequency (%)
then 7
14.9%
to 7
14.9%
residents 7
14.9%
new 4
8.5%
york 4
8.5%
city 4
8.5%
students 3
6.4%
or 3
6.4%
brooklyn 2
 
4.3%
who 1
 
2.1%
Other values (5) 5
10.6%
2023-12-09T22:09:09.004257image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
40
14.9%
e 30
11.2%
t 27
10.0%
n 25
9.3%
o 23
8.6%
s 23
8.6%
r 18
 
6.7%
i 14
 
5.2%
d 11
 
4.1%
h 8
 
3.0%
Other values (14) 50
18.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 207
77.0%
Space Separator 40
 
14.9%
Uppercase Letter 22
 
8.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 30
14.5%
t 27
13.0%
n 25
12.1%
o 23
11.1%
s 23
11.1%
r 18
8.7%
i 14
6.8%
d 11
 
5.3%
h 8
 
3.9%
y 6
 
2.9%
Other values (8) 22
10.6%
Uppercase Letter
ValueCountFrequency (%)
T 7
31.8%
C 4
18.2%
Y 4
18.2%
N 4
18.2%
B 3
13.6%
Space Separator
ValueCountFrequency (%)
40
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 229
85.1%
Common 40
 
14.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 30
13.1%
t 27
11.8%
n 25
10.9%
o 23
10.0%
s 23
10.0%
r 18
7.9%
i 14
 
6.1%
d 11
 
4.8%
h 8
 
3.5%
T 7
 
3.1%
Other values (13) 43
18.8%
Common
ValueCountFrequency (%)
40
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 269
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
40
14.9%
e 30
11.2%
t 27
10.0%
n 25
9.3%
o 23
8.6%
s 23
8.6%
r 18
 
6.7%
i 14
 
5.2%
d 11
 
4.1%
h 8
 
3.0%
Other values (14) 50
18.6%

admissionspriority35
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)20.0%
Missing435
Missing (%)98.9%
Memory size14.1 KiB
2023-12-09T22:09:09.196108image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length31
Median length31
Mean length31
Min length31

Characters and Unicode

Total characters155
Distinct characters17
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowThen to New York City residents
2nd rowThen to New York City residents
3rd rowThen to New York City residents
4th rowThen to New York City residents
5th rowThen to New York City residents
ValueCountFrequency (%)
then 5
16.7%
to 5
16.7%
new 5
16.7%
york 5
16.7%
city 5
16.7%
residents 5
16.7%
2023-12-09T22:09:09.497268image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
25
16.1%
e 20
12.9%
t 15
9.7%
n 10
 
6.5%
o 10
 
6.5%
s 10
 
6.5%
i 10
 
6.5%
r 10
 
6.5%
T 5
 
3.2%
C 5
 
3.2%
Other values (7) 35
22.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 110
71.0%
Space Separator 25
 
16.1%
Uppercase Letter 20
 
12.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 20
18.2%
t 15
13.6%
n 10
9.1%
o 10
9.1%
s 10
9.1%
i 10
9.1%
r 10
9.1%
y 5
 
4.5%
w 5
 
4.5%
k 5
 
4.5%
Other values (2) 10
9.1%
Uppercase Letter
ValueCountFrequency (%)
T 5
25.0%
C 5
25.0%
Y 5
25.0%
N 5
25.0%
Space Separator
ValueCountFrequency (%)
25
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 130
83.9%
Common 25
 
16.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 20
15.4%
t 15
11.5%
n 10
 
7.7%
o 10
 
7.7%
s 10
 
7.7%
i 10
 
7.7%
r 10
 
7.7%
T 5
 
3.8%
C 5
 
3.8%
y 5
 
3.8%
Other values (6) 30
23.1%
Common
ValueCountFrequency (%)
25
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 155
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
25
16.1%
e 20
12.9%
t 15
9.7%
n 10
 
6.5%
o 10
 
6.5%
s 10
 
6.5%
i 10
 
6.5%
r 10
 
6.5%
T 5
 
3.2%
C 5
 
3.2%
Other values (7) 35
22.6%

admissionspriority36
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing439
Missing (%)99.8%
Memory size14.0 KiB
2023-12-09T22:09:09.697276image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length65
Median length65
Mean length65
Min length65

Characters and Unicode

Total characters65
Distinct characters20
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowThen to New York City residents who attend an information session
ValueCountFrequency (%)
then 1
9.1%
to 1
9.1%
new 1
9.1%
york 1
9.1%
city 1
9.1%
residents 1
9.1%
who 1
9.1%
attend 1
9.1%
an 1
9.1%
information 1
9.1%
2023-12-09T22:09:10.016402image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
10
15.4%
n 7
10.8%
e 6
9.2%
t 6
9.2%
o 6
9.2%
s 5
7.7%
i 5
7.7%
r 3
 
4.6%
a 3
 
4.6%
w 2
 
3.1%
Other values (10) 12
18.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 51
78.5%
Space Separator 10
 
15.4%
Uppercase Letter 4
 
6.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n 7
13.7%
e 6
11.8%
t 6
11.8%
o 6
11.8%
s 5
9.8%
i 5
9.8%
r 3
5.9%
a 3
5.9%
w 2
 
3.9%
h 2
 
3.9%
Other values (5) 6
11.8%
Uppercase Letter
ValueCountFrequency (%)
T 1
25.0%
C 1
25.0%
Y 1
25.0%
N 1
25.0%
Space Separator
ValueCountFrequency (%)
10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 55
84.6%
Common 10
 
15.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
n 7
12.7%
e 6
10.9%
t 6
10.9%
o 6
10.9%
s 5
9.1%
i 5
9.1%
r 3
 
5.5%
a 3
 
5.5%
w 2
 
3.6%
h 2
 
3.6%
Other values (9) 10
18.2%
Common
ValueCountFrequency (%)
10
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 65
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
10
15.4%
n 7
10.8%
e 6
9.2%
t 6
9.2%
o 6
9.2%
s 5
7.7%
i 5
7.7%
r 3
 
4.6%
a 3
 
4.6%
w 2
 
3.1%
Other values (10) 12
18.5%

admissionspriority37
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing439
Missing (%)99.8%
Memory size13.9 KiB
2023-12-09T22:09:10.218362image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length31
Median length31
Mean length31
Min length31

Characters and Unicode

Total characters31
Distinct characters17
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowThen to New York City residents
ValueCountFrequency (%)
then 1
16.7%
to 1
16.7%
new 1
16.7%
york 1
16.7%
city 1
16.7%
residents 1
16.7%
2023-12-09T22:09:10.539163image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5
16.1%
e 4
12.9%
t 3
9.7%
n 2
 
6.5%
o 2
 
6.5%
s 2
 
6.5%
i 2
 
6.5%
r 2
 
6.5%
T 1
 
3.2%
C 1
 
3.2%
Other values (7) 7
22.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 22
71.0%
Space Separator 5
 
16.1%
Uppercase Letter 4
 
12.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 4
18.2%
t 3
13.6%
n 2
9.1%
o 2
9.1%
s 2
9.1%
i 2
9.1%
r 2
9.1%
y 1
 
4.5%
w 1
 
4.5%
k 1
 
4.5%
Other values (2) 2
9.1%
Uppercase Letter
ValueCountFrequency (%)
T 1
25.0%
C 1
25.0%
Y 1
25.0%
N 1
25.0%
Space Separator
ValueCountFrequency (%)
5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 26
83.9%
Common 5
 
16.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 4
15.4%
t 3
11.5%
n 2
 
7.7%
o 2
 
7.7%
s 2
 
7.7%
i 2
 
7.7%
r 2
 
7.7%
T 1
 
3.8%
C 1
 
3.8%
y 1
 
3.8%
Other values (6) 6
23.1%
Common
ValueCountFrequency (%)
5
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 31
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5
16.1%
e 4
12.9%
t 3
9.7%
n 2
 
6.5%
o 2
 
6.5%
s 2
 
6.5%
i 2
 
6.5%
r 2
 
6.5%
T 1
 
3.2%
C 1
 
3.2%
Other values (7) 7
22.6%

admissionspriority38
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing440
Missing (%)100.0%
Memory size3.6 KiB

admissionspriority39
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing440
Missing (%)100.0%
Memory size3.6 KiB

admissionspriority310
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing440
Missing (%)100.0%
Memory size3.6 KiB

admissionspriority41
Text

MISSING 

Distinct15
Distinct (%)9.6%
Missing284
Missing (%)64.5%
Memory size22.8 KiB
2023-12-09T22:09:10.780487image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length65
Median length31
Mean length33.26923077
Min length31

Characters and Unicode

Total characters5190
Distinct characters42
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7 ?
Unique (%)4.5%

Sample

1st rowThen to New York City residents
2nd rowThen to New York City residents
3rd rowThen to New York City residents
4th rowThen to New York City residents
5th rowThen to New York City residents
ValueCountFrequency (%)
then 156
16.0%
to 156
16.0%
residents 153
15.7%
new 125
12.9%
city 125
12.9%
york 125
12.9%
students 31
 
3.2%
or 28
 
2.9%
bronx 12
 
1.2%
district 4
 
0.4%
Other values (30) 57
 
5.9%
2023-12-09T22:09:11.158610image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
816
15.7%
e 641
12.4%
t 528
10.2%
s 390
 
7.5%
n 382
 
7.4%
o 344
 
6.6%
r 339
 
6.5%
i 308
 
5.9%
d 194
 
3.7%
h 169
 
3.3%
Other values (32) 1079
20.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 3792
73.1%
Space Separator 816
 
15.7%
Uppercase Letter 564
 
10.9%
Decimal Number 18
 
0.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 641
16.9%
t 528
13.9%
s 390
10.3%
n 382
10.1%
o 344
9.1%
r 339
8.9%
i 308
8.1%
d 194
 
5.1%
h 169
 
4.5%
k 129
 
3.4%
Other values (11) 368
9.7%
Uppercase Letter
ValueCountFrequency (%)
T 156
27.7%
C 125
22.2%
N 125
22.2%
Y 125
22.2%
B 16
 
2.8%
D 8
 
1.4%
M 3
 
0.5%
Q 2
 
0.4%
F 1
 
0.2%
L 1
 
0.2%
Other values (2) 2
 
0.4%
Decimal Number
ValueCountFrequency (%)
2 6
33.3%
1 4
22.2%
3 3
16.7%
5 1
 
5.6%
0 1
 
5.6%
6 1
 
5.6%
9 1
 
5.6%
4 1
 
5.6%
Space Separator
ValueCountFrequency (%)
816
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 4356
83.9%
Common 834
 
16.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 641
14.7%
t 528
12.1%
s 390
9.0%
n 382
8.8%
o 344
 
7.9%
r 339
 
7.8%
i 308
 
7.1%
d 194
 
4.5%
h 169
 
3.9%
T 156
 
3.6%
Other values (23) 905
20.8%
Common
ValueCountFrequency (%)
816
97.8%
2 6
 
0.7%
1 4
 
0.5%
3 3
 
0.4%
5 1
 
0.1%
0 1
 
0.1%
6 1
 
0.1%
9 1
 
0.1%
4 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5190
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
816
15.7%
e 641
12.4%
t 528
10.2%
s 390
 
7.5%
n 382
 
7.4%
o 344
 
6.6%
r 339
 
6.5%
i 308
 
5.9%
d 194
 
3.7%
h 169
 
3.3%
Other values (32) 1079
20.8%

admissionspriority42
Text

MISSING 

Distinct5
Distinct (%)29.4%
Missing423
Missing (%)96.1%
Memory size14.9 KiB
2023-12-09T22:09:11.362254image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length62
Median length31
Mean length33.76470588
Min length31

Characters and Unicode

Total characters574
Distinct characters27
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)23.5%

Sample

1st rowThen to New York City residents
2nd rowThen to Brooklyn students or residents
3rd rowThen to New York City residents
4th rowThen to New York City residents
5th rowThen to New York City residents
ValueCountFrequency (%)
then 17
16.0%
to 17
16.0%
residents 16
15.1%
new 13
12.3%
york 13
12.3%
city 13
12.3%
students 4
 
3.8%
or 3
 
2.8%
in 1
 
0.9%
catchment 1
 
0.9%
Other values (8) 8
7.5%
2023-12-09T22:09:11.702593image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
89
15.5%
e 74
12.9%
t 57
9.9%
n 42
 
7.3%
s 42
 
7.3%
o 38
 
6.6%
r 37
 
6.4%
i 32
 
5.6%
d 21
 
3.7%
h 21
 
3.7%
Other values (17) 121
21.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 426
74.2%
Space Separator 89
 
15.5%
Uppercase Letter 59
 
10.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 74
17.4%
t 57
13.4%
n 42
9.9%
s 42
9.9%
o 38
8.9%
r 37
8.7%
i 32
7.5%
d 21
 
4.9%
h 21
 
4.9%
k 14
 
3.3%
Other values (10) 48
11.3%
Uppercase Letter
ValueCountFrequency (%)
T 17
28.8%
C 13
22.0%
Y 13
22.0%
N 13
22.0%
B 2
 
3.4%
Q 1
 
1.7%
Space Separator
ValueCountFrequency (%)
89
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 485
84.5%
Common 89
 
15.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 74
15.3%
t 57
11.8%
n 42
8.7%
s 42
8.7%
o 38
 
7.8%
r 37
 
7.6%
i 32
 
6.6%
d 21
 
4.3%
h 21
 
4.3%
T 17
 
3.5%
Other values (16) 104
21.4%
Common
ValueCountFrequency (%)
89
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 574
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
89
15.5%
e 74
12.9%
t 57
9.9%
n 42
 
7.3%
s 42
 
7.3%
o 38
 
6.6%
r 37
 
6.4%
i 32
 
5.6%
d 21
 
3.7%
h 21
 
3.7%
Other values (17) 121
21.1%

admissionspriority43
Text

MISSING 

Distinct2
Distinct (%)100.0%
Missing438
Missing (%)99.5%
Memory size14.0 KiB
2023-12-09T22:09:11.900579image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length62
Median length46.5
Mean length46.5
Min length31

Characters and Unicode

Total characters93
Distinct characters24
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st rowThen to New York City residents
2nd rowThen to students who reside in the geographical catchment area
ValueCountFrequency (%)
then 2
12.5%
to 2
12.5%
new 1
 
6.2%
york 1
 
6.2%
city 1
 
6.2%
residents 1
 
6.2%
students 1
 
6.2%
who 1
 
6.2%
reside 1
 
6.2%
in 1
 
6.2%
Other values (4) 4
25.0%
2023-12-09T22:09:12.224159image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
14
15.1%
e 12
12.9%
t 9
9.7%
h 6
 
6.5%
n 6
 
6.5%
o 5
 
5.4%
s 5
 
5.4%
a 5
 
5.4%
r 5
 
5.4%
i 5
 
5.4%
Other values (14) 21
22.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 74
79.6%
Space Separator 14
 
15.1%
Uppercase Letter 5
 
5.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 12
16.2%
t 9
12.2%
h 6
8.1%
n 6
8.1%
o 5
 
6.8%
s 5
 
6.8%
a 5
 
6.8%
r 5
 
6.8%
i 5
 
6.8%
d 3
 
4.1%
Other values (9) 13
17.6%
Uppercase Letter
ValueCountFrequency (%)
T 2
40.0%
C 1
20.0%
Y 1
20.0%
N 1
20.0%
Space Separator
ValueCountFrequency (%)
14
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 79
84.9%
Common 14
 
15.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 12
15.2%
t 9
11.4%
h 6
 
7.6%
n 6
 
7.6%
o 5
 
6.3%
s 5
 
6.3%
a 5
 
6.3%
r 5
 
6.3%
i 5
 
6.3%
d 3
 
3.8%
Other values (13) 18
22.8%
Common
ValueCountFrequency (%)
14
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 93
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
14
15.1%
e 12
12.9%
t 9
9.7%
h 6
 
6.5%
n 6
 
6.5%
o 5
 
5.4%
s 5
 
5.4%
a 5
 
5.4%
r 5
 
5.4%
i 5
 
5.4%
Other values (14) 21
22.6%

admissionspriority44
Text

MISSING 

Distinct2
Distinct (%)66.7%
Missing437
Missing (%)99.3%
Memory size14.1 KiB
2023-12-09T22:09:12.425680image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length65
Median length31
Mean length42.33333333
Min length31

Characters and Unicode

Total characters127
Distinct characters20
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)33.3%

Sample

1st rowThen to New York City residents
2nd rowThen to New York City residents who attend an information session
3rd rowThen to New York City residents
ValueCountFrequency (%)
then 3
13.0%
to 3
13.0%
new 3
13.0%
york 3
13.0%
city 3
13.0%
residents 3
13.0%
who 1
 
4.3%
attend 1
 
4.3%
an 1
 
4.3%
information 1
 
4.3%
2023-12-09T22:09:14.192925image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
20
15.7%
e 14
11.0%
t 12
9.4%
n 11
8.7%
o 10
 
7.9%
i 9
 
7.1%
s 9
 
7.1%
r 7
 
5.5%
w 4
 
3.1%
d 4
 
3.1%
Other values (10) 27
21.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 95
74.8%
Space Separator 20
 
15.7%
Uppercase Letter 12
 
9.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 14
14.7%
t 12
12.6%
n 11
11.6%
o 10
10.5%
i 9
9.5%
s 9
9.5%
r 7
7.4%
w 4
 
4.2%
d 4
 
4.2%
h 4
 
4.2%
Other values (5) 11
11.6%
Uppercase Letter
ValueCountFrequency (%)
T 3
25.0%
C 3
25.0%
Y 3
25.0%
N 3
25.0%
Space Separator
ValueCountFrequency (%)
20
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 107
84.3%
Common 20
 
15.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 14
13.1%
t 12
11.2%
n 11
10.3%
o 10
9.3%
i 9
 
8.4%
s 9
 
8.4%
r 7
 
6.5%
w 4
 
3.7%
d 4
 
3.7%
h 4
 
3.7%
Other values (9) 23
21.5%
Common
ValueCountFrequency (%)
20
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 127
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
20
15.7%
e 14
11.0%
t 12
9.4%
n 11
8.7%
o 10
 
7.9%
i 9
 
7.1%
s 9
 
7.1%
r 7
 
5.5%
w 4
 
3.1%
d 4
 
3.1%
Other values (10) 27
21.3%

admissionspriority45
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing440
Missing (%)100.0%
Memory size3.6 KiB

admissionspriority46
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing439
Missing (%)99.8%
Memory size13.9 KiB
2023-12-09T22:09:14.386711image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length50
Median length50
Mean length50
Min length50

Characters and Unicode

Total characters50
Distinct characters19
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowThen to Districts 3, 5 and 6 students or residents
ValueCountFrequency (%)
then 1
10.0%
to 1
10.0%
districts 1
10.0%
3 1
10.0%
5 1
10.0%
and 1
10.0%
6 1
10.0%
students 1
10.0%
or 1
10.0%
residents 1
10.0%
2023-12-09T22:09:14.698657image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9
18.0%
s 6
12.0%
t 6
12.0%
e 4
8.0%
n 4
8.0%
i 3
 
6.0%
d 3
 
6.0%
r 3
 
6.0%
o 2
 
4.0%
, 1
 
2.0%
Other values (9) 9
18.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 35
70.0%
Space Separator 9
 
18.0%
Decimal Number 3
 
6.0%
Uppercase Letter 2
 
4.0%
Other Punctuation 1
 
2.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
s 6
17.1%
t 6
17.1%
e 4
11.4%
n 4
11.4%
i 3
8.6%
d 3
8.6%
r 3
8.6%
o 2
 
5.7%
a 1
 
2.9%
c 1
 
2.9%
Other values (2) 2
 
5.7%
Decimal Number
ValueCountFrequency (%)
6 1
33.3%
5 1
33.3%
3 1
33.3%
Uppercase Letter
ValueCountFrequency (%)
T 1
50.0%
D 1
50.0%
Space Separator
ValueCountFrequency (%)
9
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 37
74.0%
Common 13
 
26.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
s 6
16.2%
t 6
16.2%
e 4
10.8%
n 4
10.8%
i 3
8.1%
d 3
8.1%
r 3
8.1%
o 2
 
5.4%
a 1
 
2.7%
T 1
 
2.7%
Other values (4) 4
10.8%
Common
ValueCountFrequency (%)
9
69.2%
, 1
 
7.7%
6 1
 
7.7%
5 1
 
7.7%
3 1
 
7.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 50
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
9
18.0%
s 6
12.0%
t 6
12.0%
e 4
8.0%
n 4
8.0%
i 3
 
6.0%
d 3
 
6.0%
r 3
 
6.0%
o 2
 
4.0%
, 1
 
2.0%
Other values (9) 9
18.0%

admissionspriority47
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing440
Missing (%)100.0%
Memory size3.6 KiB

admissionspriority48
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing440
Missing (%)100.0%
Memory size3.6 KiB

admissionspriority49
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing440
Missing (%)100.0%
Memory size3.6 KiB

admissionspriority410
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing440
Missing (%)100.0%
Memory size3.6 KiB

admissionspriority51
Text

MISSING 

Distinct8
Distinct (%)24.2%
Missing407
Missing (%)92.5%
Memory size15.8 KiB
2023-12-09T22:09:14.902488image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length53
Median length31
Mean length34.03030303
Min length31

Characters and Unicode

Total characters1123
Distinct characters32
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)15.2%

Sample

1st rowThen to Brooklyn students or residents
2nd rowThen to New York City residents
3rd rowThen to Brooklyn students or residents
4th rowThen to New York City residents
5th rowThen to New York City residents
ValueCountFrequency (%)
then 33
16.3%
to 33
16.3%
residents 33
16.3%
new 21
10.3%
york 21
10.3%
city 21
10.3%
students 12
 
5.9%
or 12
 
5.9%
brooklyn 5
 
2.5%
manhattan 3
 
1.5%
Other values (9) 9
 
4.4%
2023-12-09T22:09:15.238978image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
170
15.1%
e 134
11.9%
t 121
10.8%
s 94
8.4%
n 92
8.2%
o 77
 
6.9%
r 74
 
6.6%
i 58
 
5.2%
d 46
 
4.1%
h 36
 
3.2%
Other values (22) 221
19.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 837
74.5%
Space Separator 170
 
15.1%
Uppercase Letter 107
 
9.5%
Decimal Number 8
 
0.7%
Other Punctuation 1
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 134
16.0%
t 121
14.5%
s 94
11.2%
n 92
11.0%
o 77
9.2%
r 74
8.8%
i 58
6.9%
d 46
 
5.5%
h 36
 
4.3%
k 26
 
3.1%
Other values (7) 79
9.4%
Uppercase Letter
ValueCountFrequency (%)
T 33
30.8%
Y 21
19.6%
N 21
19.6%
C 20
18.7%
B 6
 
5.6%
M 3
 
2.8%
D 2
 
1.9%
Q 1
 
0.9%
Decimal Number
ValueCountFrequency (%)
2 3
37.5%
3 2
25.0%
7 1
 
12.5%
4 1
 
12.5%
0 1
 
12.5%
Space Separator
ValueCountFrequency (%)
170
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 944
84.1%
Common 179
 
15.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 134
14.2%
t 121
12.8%
s 94
10.0%
n 92
9.7%
o 77
8.2%
r 74
7.8%
i 58
 
6.1%
d 46
 
4.9%
h 36
 
3.8%
T 33
 
3.5%
Other values (15) 179
19.0%
Common
ValueCountFrequency (%)
170
95.0%
2 3
 
1.7%
3 2
 
1.1%
7 1
 
0.6%
4 1
 
0.6%
, 1
 
0.6%
0 1
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1123
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
170
15.1%
e 134
11.9%
t 121
10.8%
s 94
8.4%
n 92
8.2%
o 77
 
6.9%
r 74
 
6.6%
i 58
 
5.2%
d 46
 
4.1%
h 36
 
3.2%
Other values (22) 221
19.7%

admissionspriority52
Text

MISSING 

Distinct2
Distinct (%)66.7%
Missing437
Missing (%)99.3%
Memory size14.0 KiB
2023-12-09T22:09:15.427928image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length38
Median length31
Mean length33.33333333
Min length31

Characters and Unicode

Total characters100
Distinct characters20
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)33.3%

Sample

1st rowThen to New York City residents
2nd rowThen to New York City residents
3rd rowThen to Brooklyn students or residents
ValueCountFrequency (%)
then 3
16.7%
to 3
16.7%
residents 3
16.7%
new 2
11.1%
york 2
11.1%
city 2
11.1%
brooklyn 1
 
5.6%
students 1
 
5.6%
or 1
 
5.6%
2023-12-09T22:09:15.752933image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
15
15.0%
e 12
12.0%
t 10
10.0%
n 8
 
8.0%
o 8
 
8.0%
s 8
 
8.0%
r 7
 
7.0%
i 5
 
5.0%
d 4
 
4.0%
k 3
 
3.0%
Other values (10) 20
20.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 75
75.0%
Space Separator 15
 
15.0%
Uppercase Letter 10
 
10.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 12
16.0%
t 10
13.3%
n 8
10.7%
o 8
10.7%
s 8
10.7%
r 7
9.3%
i 5
6.7%
d 4
 
5.3%
k 3
 
4.0%
y 3
 
4.0%
Other values (4) 7
9.3%
Uppercase Letter
ValueCountFrequency (%)
T 3
30.0%
C 2
20.0%
Y 2
20.0%
N 2
20.0%
B 1
 
10.0%
Space Separator
ValueCountFrequency (%)
15
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 85
85.0%
Common 15
 
15.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 12
14.1%
t 10
11.8%
n 8
9.4%
o 8
9.4%
s 8
9.4%
r 7
8.2%
i 5
 
5.9%
d 4
 
4.7%
k 3
 
3.5%
y 3
 
3.5%
Other values (9) 17
20.0%
Common
ValueCountFrequency (%)
15
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 100
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
15
15.0%
e 12
12.0%
t 10
10.0%
n 8
 
8.0%
o 8
 
8.0%
s 8
 
8.0%
r 7
 
7.0%
i 5
 
5.0%
d 4
 
4.0%
k 3
 
3.0%
Other values (10) 20
20.0%

admissionspriority53
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing439
Missing (%)99.8%
Memory size13.9 KiB
2023-12-09T22:09:15.940166image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length38
Median length38
Mean length38
Min length38

Characters and Unicode

Total characters38
Distinct characters16
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowThen to Brooklyn students or residents
ValueCountFrequency (%)
then 1
16.7%
to 1
16.7%
brooklyn 1
16.7%
students 1
16.7%
or 1
16.7%
residents 1
16.7%
2023-12-09T22:09:16.250851image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5
13.2%
e 4
10.5%
n 4
10.5%
t 4
10.5%
o 4
10.5%
s 4
10.5%
r 3
7.9%
d 2
 
5.3%
T 1
 
2.6%
h 1
 
2.6%
Other values (6) 6
15.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 31
81.6%
Space Separator 5
 
13.2%
Uppercase Letter 2
 
5.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 4
12.9%
n 4
12.9%
t 4
12.9%
o 4
12.9%
s 4
12.9%
r 3
9.7%
d 2
6.5%
h 1
 
3.2%
k 1
 
3.2%
l 1
 
3.2%
Other values (3) 3
9.7%
Uppercase Letter
ValueCountFrequency (%)
T 1
50.0%
B 1
50.0%
Space Separator
ValueCountFrequency (%)
5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 33
86.8%
Common 5
 
13.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 4
12.1%
n 4
12.1%
t 4
12.1%
o 4
12.1%
s 4
12.1%
r 3
9.1%
d 2
 
6.1%
T 1
 
3.0%
h 1
 
3.0%
B 1
 
3.0%
Other values (5) 5
15.2%
Common
ValueCountFrequency (%)
5
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 38
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5
13.2%
e 4
10.5%
n 4
10.5%
t 4
10.5%
o 4
10.5%
s 4
10.5%
r 3
7.9%
d 2
 
5.3%
T 1
 
2.6%
h 1
 
2.6%
Other values (6) 6
15.8%

admissionspriority54
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing439
Missing (%)99.8%
Memory size13.9 KiB
2023-12-09T22:09:16.439672image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length41
Median length41
Mean length41
Min length41

Characters and Unicode

Total characters41
Distinct characters16
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowThen to District 14 students or residents
ValueCountFrequency (%)
then 1
14.3%
to 1
14.3%
district 1
14.3%
14 1
14.3%
students 1
14.3%
or 1
14.3%
residents 1
14.3%
2023-12-09T22:09:16.742327image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6
14.6%
t 6
14.6%
s 5
12.2%
e 4
9.8%
n 3
7.3%
i 3
7.3%
r 3
7.3%
o 2
 
4.9%
d 2
 
4.9%
T 1
 
2.4%
Other values (6) 6
14.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 31
75.6%
Space Separator 6
 
14.6%
Uppercase Letter 2
 
4.9%
Decimal Number 2
 
4.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 6
19.4%
s 5
16.1%
e 4
12.9%
n 3
9.7%
i 3
9.7%
r 3
9.7%
o 2
 
6.5%
d 2
 
6.5%
h 1
 
3.2%
c 1
 
3.2%
Uppercase Letter
ValueCountFrequency (%)
T 1
50.0%
D 1
50.0%
Decimal Number
ValueCountFrequency (%)
1 1
50.0%
4 1
50.0%
Space Separator
ValueCountFrequency (%)
6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 33
80.5%
Common 8
 
19.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 6
18.2%
s 5
15.2%
e 4
12.1%
n 3
9.1%
i 3
9.1%
r 3
9.1%
o 2
 
6.1%
d 2
 
6.1%
T 1
 
3.0%
h 1
 
3.0%
Other values (3) 3
9.1%
Common
ValueCountFrequency (%)
6
75.0%
1 1
 
12.5%
4 1
 
12.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 41
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6
14.6%
t 6
14.6%
s 5
12.2%
e 4
9.8%
n 3
7.3%
i 3
7.3%
r 3
7.3%
o 2
 
4.9%
d 2
 
4.9%
T 1
 
2.4%
Other values (6) 6
14.6%

admissionspriority55
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing440
Missing (%)100.0%
Memory size3.6 KiB

admissionspriority56
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing439
Missing (%)99.8%
Memory size13.9 KiB
2023-12-09T22:09:16.931902image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length31
Median length31
Mean length31
Min length31

Characters and Unicode

Total characters31
Distinct characters17
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowThen to New York City residents
ValueCountFrequency (%)
then 1
16.7%
to 1
16.7%
new 1
16.7%
york 1
16.7%
city 1
16.7%
residents 1
16.7%
2023-12-09T22:09:17.242101image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5
16.1%
e 4
12.9%
t 3
9.7%
n 2
 
6.5%
o 2
 
6.5%
s 2
 
6.5%
i 2
 
6.5%
r 2
 
6.5%
T 1
 
3.2%
C 1
 
3.2%
Other values (7) 7
22.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 22
71.0%
Space Separator 5
 
16.1%
Uppercase Letter 4
 
12.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 4
18.2%
t 3
13.6%
n 2
9.1%
o 2
9.1%
s 2
9.1%
i 2
9.1%
r 2
9.1%
y 1
 
4.5%
w 1
 
4.5%
k 1
 
4.5%
Other values (2) 2
9.1%
Uppercase Letter
ValueCountFrequency (%)
T 1
25.0%
C 1
25.0%
Y 1
25.0%
N 1
25.0%
Space Separator
ValueCountFrequency (%)
5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 26
83.9%
Common 5
 
16.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 4
15.4%
t 3
11.5%
n 2
 
7.7%
o 2
 
7.7%
s 2
 
7.7%
i 2
 
7.7%
r 2
 
7.7%
T 1
 
3.8%
C 1
 
3.8%
y 1
 
3.8%
Other values (6) 6
23.1%
Common
ValueCountFrequency (%)
5
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 31
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5
16.1%
e 4
12.9%
t 3
9.7%
n 2
 
6.5%
o 2
 
6.5%
s 2
 
6.5%
i 2
 
6.5%
r 2
 
6.5%
T 1
 
3.2%
C 1
 
3.2%
Other values (7) 7
22.6%

admissionspriority57
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing440
Missing (%)100.0%
Memory size3.6 KiB

admissionspriority58
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing440
Missing (%)100.0%
Memory size3.6 KiB

admissionspriority59
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing440
Missing (%)100.0%
Memory size3.6 KiB

admissionspriority510
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing440
Missing (%)100.0%
Memory size3.6 KiB

admissionspriority61
Text

MISSING 

Distinct3
Distinct (%)25.0%
Missing428
Missing (%)97.3%
Memory size14.5 KiB
2023-12-09T22:09:17.438713image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length38
Median length31
Mean length32
Min length31

Characters and Unicode

Total characters384
Distinct characters21
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)16.7%

Sample

1st rowThen to New York City residents
2nd rowThen to New York City residents
3rd rowThen to New York City residents
4th rowThen to New York City residents
5th rowThen to New York City residents
ValueCountFrequency (%)
then 12
16.7%
to 12
16.7%
residents 12
16.7%
new 10
13.9%
york 10
13.9%
city 10
13.9%
students 2
 
2.8%
or 2
 
2.8%
queens 1
 
1.4%
brooklyn 1
 
1.4%
2023-12-09T22:09:17.770638image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
60
15.6%
e 50
13.0%
t 38
9.9%
s 29
 
7.6%
n 28
 
7.3%
o 26
 
6.8%
r 25
 
6.5%
i 22
 
5.7%
d 14
 
3.6%
h 12
 
3.1%
Other values (11) 80
20.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 280
72.9%
Space Separator 60
 
15.6%
Uppercase Letter 44
 
11.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 50
17.9%
t 38
13.6%
s 29
10.4%
n 28
10.0%
o 26
9.3%
r 25
8.9%
i 22
7.9%
d 14
 
5.0%
h 12
 
4.3%
k 11
 
3.9%
Other values (4) 25
8.9%
Uppercase Letter
ValueCountFrequency (%)
T 12
27.3%
C 10
22.7%
Y 10
22.7%
N 10
22.7%
Q 1
 
2.3%
B 1
 
2.3%
Space Separator
ValueCountFrequency (%)
60
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 324
84.4%
Common 60
 
15.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 50
15.4%
t 38
11.7%
s 29
9.0%
n 28
8.6%
o 26
 
8.0%
r 25
 
7.7%
i 22
 
6.8%
d 14
 
4.3%
h 12
 
3.7%
T 12
 
3.7%
Other values (10) 68
21.0%
Common
ValueCountFrequency (%)
60
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 384
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
60
15.6%
e 50
13.0%
t 38
9.9%
s 29
 
7.6%
n 28
 
7.3%
o 26
 
6.8%
r 25
 
6.5%
i 22
 
5.7%
d 14
 
3.6%
h 12
 
3.1%
Other values (11) 80
20.8%

admissionspriority62
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing439
Missing (%)99.8%
Memory size13.9 KiB
2023-12-09T22:09:17.968144image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length31
Median length31
Mean length31
Min length31

Characters and Unicode

Total characters31
Distinct characters17
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowThen to New York City residents
ValueCountFrequency (%)
then 1
16.7%
to 1
16.7%
new 1
16.7%
york 1
16.7%
city 1
16.7%
residents 1
16.7%
2023-12-09T22:09:18.292362image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5
16.1%
e 4
12.9%
t 3
9.7%
n 2
 
6.5%
o 2
 
6.5%
s 2
 
6.5%
i 2
 
6.5%
r 2
 
6.5%
T 1
 
3.2%
C 1
 
3.2%
Other values (7) 7
22.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 22
71.0%
Space Separator 5
 
16.1%
Uppercase Letter 4
 
12.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 4
18.2%
t 3
13.6%
n 2
9.1%
o 2
9.1%
s 2
9.1%
i 2
9.1%
r 2
9.1%
y 1
 
4.5%
w 1
 
4.5%
k 1
 
4.5%
Other values (2) 2
9.1%
Uppercase Letter
ValueCountFrequency (%)
T 1
25.0%
C 1
25.0%
Y 1
25.0%
N 1
25.0%
Space Separator
ValueCountFrequency (%)
5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 26
83.9%
Common 5
 
16.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 4
15.4%
t 3
11.5%
n 2
 
7.7%
o 2
 
7.7%
s 2
 
7.7%
i 2
 
7.7%
r 2
 
7.7%
T 1
 
3.8%
C 1
 
3.8%
y 1
 
3.8%
Other values (6) 6
23.1%
Common
ValueCountFrequency (%)
5
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 31
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5
16.1%
e 4
12.9%
t 3
9.7%
n 2
 
6.5%
o 2
 
6.5%
s 2
 
6.5%
i 2
 
6.5%
r 2
 
6.5%
T 1
 
3.2%
C 1
 
3.2%
Other values (7) 7
22.6%

admissionspriority63
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing439
Missing (%)99.8%
Memory size13.9 KiB
2023-12-09T22:09:18.485311image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length31
Median length31
Mean length31
Min length31

Characters and Unicode

Total characters31
Distinct characters17
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowThen to New York City residents
ValueCountFrequency (%)
then 1
16.7%
to 1
16.7%
new 1
16.7%
york 1
16.7%
city 1
16.7%
residents 1
16.7%
2023-12-09T22:09:18.796746image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5
16.1%
e 4
12.9%
t 3
9.7%
n 2
 
6.5%
o 2
 
6.5%
s 2
 
6.5%
i 2
 
6.5%
r 2
 
6.5%
T 1
 
3.2%
C 1
 
3.2%
Other values (7) 7
22.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 22
71.0%
Space Separator 5
 
16.1%
Uppercase Letter 4
 
12.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 4
18.2%
t 3
13.6%
n 2
9.1%
o 2
9.1%
s 2
9.1%
i 2
9.1%
r 2
9.1%
y 1
 
4.5%
w 1
 
4.5%
k 1
 
4.5%
Other values (2) 2
9.1%
Uppercase Letter
ValueCountFrequency (%)
T 1
25.0%
C 1
25.0%
Y 1
25.0%
N 1
25.0%
Space Separator
ValueCountFrequency (%)
5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 26
83.9%
Common 5
 
16.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 4
15.4%
t 3
11.5%
n 2
 
7.7%
o 2
 
7.7%
s 2
 
7.7%
i 2
 
7.7%
r 2
 
7.7%
T 1
 
3.8%
C 1
 
3.8%
y 1
 
3.8%
Other values (6) 6
23.1%
Common
ValueCountFrequency (%)
5
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 31
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5
16.1%
e 4
12.9%
t 3
9.7%
n 2
 
6.5%
o 2
 
6.5%
s 2
 
6.5%
i 2
 
6.5%
r 2
 
6.5%
T 1
 
3.2%
C 1
 
3.2%
Other values (7) 7
22.6%

admissionspriority64
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing439
Missing (%)99.8%
Memory size13.9 KiB
2023-12-09T22:09:18.993719image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length38
Median length38
Mean length38
Min length38

Characters and Unicode

Total characters38
Distinct characters16
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowThen to Brooklyn students or residents
ValueCountFrequency (%)
then 1
16.7%
to 1
16.7%
brooklyn 1
16.7%
students 1
16.7%
or 1
16.7%
residents 1
16.7%
2023-12-09T22:09:19.301326image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5
13.2%
e 4
10.5%
n 4
10.5%
t 4
10.5%
o 4
10.5%
s 4
10.5%
r 3
7.9%
d 2
 
5.3%
T 1
 
2.6%
h 1
 
2.6%
Other values (6) 6
15.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 31
81.6%
Space Separator 5
 
13.2%
Uppercase Letter 2
 
5.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 4
12.9%
n 4
12.9%
t 4
12.9%
o 4
12.9%
s 4
12.9%
r 3
9.7%
d 2
6.5%
h 1
 
3.2%
k 1
 
3.2%
l 1
 
3.2%
Other values (3) 3
9.7%
Uppercase Letter
ValueCountFrequency (%)
T 1
50.0%
B 1
50.0%
Space Separator
ValueCountFrequency (%)
5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 33
86.8%
Common 5
 
13.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 4
12.1%
n 4
12.1%
t 4
12.1%
o 4
12.1%
s 4
12.1%
r 3
9.1%
d 2
 
6.1%
T 1
 
3.0%
h 1
 
3.0%
B 1
 
3.0%
Other values (5) 5
15.2%
Common
ValueCountFrequency (%)
5
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 38
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5
13.2%
e 4
10.5%
n 4
10.5%
t 4
10.5%
o 4
10.5%
s 4
10.5%
r 3
7.9%
d 2
 
5.3%
T 1
 
2.6%
h 1
 
2.6%
Other values (6) 6
15.8%

admissionspriority65
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing440
Missing (%)100.0%
Memory size3.6 KiB

admissionspriority66
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing440
Missing (%)100.0%
Memory size3.6 KiB

admissionspriority67
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing440
Missing (%)100.0%
Memory size3.6 KiB

admissionspriority68
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing440
Missing (%)100.0%
Memory size3.6 KiB

admissionspriority69
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing440
Missing (%)100.0%
Memory size3.6 KiB

admissionspriority610
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing440
Missing (%)100.0%
Memory size3.6 KiB

admissionspriority71
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)50.0%
Missing438
Missing (%)99.5%
Memory size14.0 KiB
2023-12-09T22:09:19.488627image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length31
Median length31
Mean length31
Min length31

Characters and Unicode

Total characters62
Distinct characters17
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowThen to New York City residents
2nd rowThen to New York City residents
ValueCountFrequency (%)
then 2
16.7%
to 2
16.7%
new 2
16.7%
york 2
16.7%
city 2
16.7%
residents 2
16.7%
2023-12-09T22:09:19.784526image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
10
16.1%
e 8
12.9%
t 6
9.7%
n 4
 
6.5%
o 4
 
6.5%
s 4
 
6.5%
i 4
 
6.5%
r 4
 
6.5%
T 2
 
3.2%
C 2
 
3.2%
Other values (7) 14
22.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 44
71.0%
Space Separator 10
 
16.1%
Uppercase Letter 8
 
12.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 8
18.2%
t 6
13.6%
n 4
9.1%
o 4
9.1%
s 4
9.1%
i 4
9.1%
r 4
9.1%
y 2
 
4.5%
w 2
 
4.5%
k 2
 
4.5%
Other values (2) 4
9.1%
Uppercase Letter
ValueCountFrequency (%)
T 2
25.0%
C 2
25.0%
Y 2
25.0%
N 2
25.0%
Space Separator
ValueCountFrequency (%)
10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 52
83.9%
Common 10
 
16.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 8
15.4%
t 6
11.5%
n 4
 
7.7%
o 4
 
7.7%
s 4
 
7.7%
i 4
 
7.7%
r 4
 
7.7%
T 2
 
3.8%
C 2
 
3.8%
y 2
 
3.8%
Other values (6) 12
23.1%
Common
ValueCountFrequency (%)
10
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 62
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
10
16.1%
e 8
12.9%
t 6
9.7%
n 4
 
6.5%
o 4
 
6.5%
s 4
 
6.5%
i 4
 
6.5%
r 4
 
6.5%
T 2
 
3.2%
C 2
 
3.2%
Other values (7) 14
22.6%

admissionspriority72
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing440
Missing (%)100.0%
Memory size3.6 KiB

admissionspriority73
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing440
Missing (%)100.0%
Memory size3.6 KiB

admissionspriority74
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing439
Missing (%)99.8%
Memory size13.9 KiB
2023-12-09T22:09:19.973304image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length31
Median length31
Mean length31
Min length31

Characters and Unicode

Total characters31
Distinct characters17
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowThen to New York City residents
ValueCountFrequency (%)
then 1
16.7%
to 1
16.7%
new 1
16.7%
york 1
16.7%
city 1
16.7%
residents 1
16.7%
2023-12-09T22:09:20.281396image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5
16.1%
e 4
12.9%
t 3
9.7%
n 2
 
6.5%
o 2
 
6.5%
s 2
 
6.5%
i 2
 
6.5%
r 2
 
6.5%
T 1
 
3.2%
C 1
 
3.2%
Other values (7) 7
22.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 22
71.0%
Space Separator 5
 
16.1%
Uppercase Letter 4
 
12.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 4
18.2%
t 3
13.6%
n 2
9.1%
o 2
9.1%
s 2
9.1%
i 2
9.1%
r 2
9.1%
y 1
 
4.5%
w 1
 
4.5%
k 1
 
4.5%
Other values (2) 2
9.1%
Uppercase Letter
ValueCountFrequency (%)
T 1
25.0%
C 1
25.0%
Y 1
25.0%
N 1
25.0%
Space Separator
ValueCountFrequency (%)
5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 26
83.9%
Common 5
 
16.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 4
15.4%
t 3
11.5%
n 2
 
7.7%
o 2
 
7.7%
s 2
 
7.7%
i 2
 
7.7%
r 2
 
7.7%
T 1
 
3.8%
C 1
 
3.8%
y 1
 
3.8%
Other values (6) 6
23.1%
Common
ValueCountFrequency (%)
5
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 31
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5
16.1%
e 4
12.9%
t 3
9.7%
n 2
 
6.5%
o 2
 
6.5%
s 2
 
6.5%
i 2
 
6.5%
r 2
 
6.5%
T 1
 
3.2%
C 1
 
3.2%
Other values (7) 7
22.6%

admissionspriority75
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing440
Missing (%)100.0%
Memory size3.6 KiB

admissionspriority76
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing440
Missing (%)100.0%
Memory size3.6 KiB

admissionspriority77
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing440
Missing (%)100.0%
Memory size3.6 KiB

admissionspriority78
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing440
Missing (%)100.0%
Memory size3.6 KiB

admissionspriority79
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing440
Missing (%)100.0%
Memory size3.6 KiB

admissionspriority710
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing440
Missing (%)100.0%
Memory size3.6 KiB

eligibility1
Text

MISSING 

Distinct35
Distinct (%)53.8%
Missing375
Missing (%)85.2%
Memory size25.6 KiB
2023-12-09T22:09:20.588851image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length303
Median length265
Mean length131.2923077
Min length26

Characters and Unicode

Total characters8534
Distinct characters64
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24 ?
Unique (%)36.9%

Sample

1st rowFor Current 8th Grade Students – Open only to students who are at least 15 1/2 years of age and entering high school for the first time. For Other Students – Open only to students who are at least 16 years of age and have attended another high school for at least one year
2nd rowOpen only to female students
3rd rowOpen only to New York City residents living in the United States four years or fewer whose home language is Spanish and are English Language Learners per New York City Department of Education guidelines scoring at the Entering, Emerging, or Transitioning levels on the NYSESLAT, NYSITELL, or LAB-R.
4th rowFor Current 8th Grade Students – Open only to students who are at least 15 years of age and entering high school for the first time. For Other Students – Students must be 17-21 years of age, have a minimum of 10 credits, have passed 1 Regents exam, and have attended high school for at least one year.
5th rowOpen only to female students
ValueCountFrequency (%)
students 65
 
4.5%
to 62
 
4.3%
only 59
 
4.1%
open 56
 
3.9%
or 56
 
3.9%
the 55
 
3.8%
of 40
 
2.8%
for 36
 
2.5%
at 35
 
2.4%
are 32
 
2.2%
Other values (130) 933
65.3%
2023-12-09T22:09:21.058064image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1364
16.0%
e 881
 
10.3%
n 629
 
7.4%
t 602
 
7.1%
o 511
 
6.0%
r 486
 
5.7%
s 443
 
5.2%
i 419
 
4.9%
a 408
 
4.8%
l 259
 
3.0%
Other values (54) 2532
29.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 6273
73.5%
Space Separator 1364
 
16.0%
Uppercase Letter 707
 
8.3%
Other Punctuation 92
 
1.1%
Decimal Number 53
 
0.6%
Dash Punctuation 33
 
0.4%
Close Punctuation 6
 
0.1%
Open Punctuation 6
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 881
14.0%
n 629
10.0%
t 602
9.6%
o 511
 
8.1%
r 486
 
7.7%
s 443
 
7.1%
i 419
 
6.7%
a 408
 
6.5%
l 259
 
4.1%
g 251
 
4.0%
Other values (15) 1384
22.1%
Uppercase Letter
ValueCountFrequency (%)
E 105
14.9%
L 98
13.9%
S 90
12.7%
O 62
8.8%
N 61
8.6%
Y 61
8.6%
T 43
6.1%
C 40
 
5.7%
A 26
 
3.7%
B 23
 
3.3%
Other values (11) 98
13.9%
Decimal Number
ValueCountFrequency (%)
1 20
37.7%
5 10
18.9%
6 8
 
15.1%
8 7
 
13.2%
2 3
 
5.7%
0 3
 
5.7%
7 1
 
1.9%
9 1
 
1.9%
Other Punctuation
ValueCountFrequency (%)
, 58
63.0%
. 28
30.4%
/ 4
 
4.3%
% 2
 
2.2%
Dash Punctuation
ValueCountFrequency (%)
- 21
63.6%
– 8
 
24.2%
— 4
 
12.1%
Space Separator
ValueCountFrequency (%)
1364
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 6980
81.8%
Common 1554
 
18.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 881
12.6%
n 629
 
9.0%
t 602
 
8.6%
o 511
 
7.3%
r 486
 
7.0%
s 443
 
6.3%
i 419
 
6.0%
a 408
 
5.8%
l 259
 
3.7%
g 251
 
3.6%
Other values (36) 2091
30.0%
Common
ValueCountFrequency (%)
1364
87.8%
, 58
 
3.7%
. 28
 
1.8%
- 21
 
1.4%
1 20
 
1.3%
5 10
 
0.6%
– 8
 
0.5%
6 8
 
0.5%
8 7
 
0.5%
) 6
 
0.4%
Other values (8) 24
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8510
99.7%
None 12
 
0.1%
Punctuation 12
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1364
16.0%
e 881
 
10.4%
n 629
 
7.4%
t 602
 
7.1%
o 511
 
6.0%
r 486
 
5.7%
s 443
 
5.2%
i 419
 
4.9%
a 408
 
4.8%
l 259
 
3.0%
Other values (51) 2508
29.5%
None
ValueCountFrequency (%)
 12
100.0%
Punctuation
ValueCountFrequency (%)
– 8
66.7%
— 4
33.3%

eligibility2
Text

MISSING 

Distinct15
Distinct (%)53.6%
Missing412
Missing (%)93.6%
Memory size16.0 KiB
2023-12-09T22:09:21.321253image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length163
Median length78
Mean length53.57142857
Min length28

Characters and Unicode

Total characters1500
Distinct characters43
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10 ?
Unique (%)35.7%

Sample

1st rowOpen only to continuing 8th graders
2nd rowOpen only to continuing 8th graders
3rd rowOpen only to continuing 8th graders
4th rowOpen only to continuing 8th graders.
5th rowOpen only to Bronx students or residents
ValueCountFrequency (%)
open 28
 
11.1%
to 28
 
11.1%
only 27
 
10.7%
students 17
 
6.7%
residents 11
 
4.3%
or 10
 
4.0%
language 9
 
3.6%
8th 9
 
3.6%
continuing 9
 
3.6%
graders 9
 
3.6%
Other values (37) 96
37.9%
2023-12-09T22:09:21.719094image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
225
15.0%
n 157
 
10.5%
e 153
 
10.2%
t 113
 
7.5%
o 108
 
7.2%
s 101
 
6.7%
i 79
 
5.3%
r 63
 
4.2%
a 53
 
3.5%
l 53
 
3.5%
Other values (33) 395
26.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1189
79.3%
Space Separator 225
 
15.0%
Uppercase Letter 67
 
4.5%
Decimal Number 10
 
0.7%
Other Punctuation 5
 
0.3%
Close Punctuation 2
 
0.1%
Open Punctuation 2
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n 157
13.2%
e 153
12.9%
t 113
9.5%
o 108
9.1%
s 101
 
8.5%
i 79
 
6.6%
r 63
 
5.3%
a 53
 
4.5%
l 53
 
4.5%
d 48
 
4.0%
Other values (13) 261
22.0%
Uppercase Letter
ValueCountFrequency (%)
O 28
41.8%
S 7
 
10.4%
C 6
 
9.0%
B 5
 
7.5%
E 5
 
7.5%
Q 4
 
6.0%
U 3
 
4.5%
M 2
 
3.0%
N 2
 
3.0%
Y 2
 
3.0%
Other values (2) 3
 
4.5%
Other Punctuation
ValueCountFrequency (%)
, 2
40.0%
: 2
40.0%
. 1
20.0%
Decimal Number
ValueCountFrequency (%)
8 9
90.0%
4 1
 
10.0%
Space Separator
ValueCountFrequency (%)
225
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1256
83.7%
Common 244
 
16.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
n 157
12.5%
e 153
12.2%
t 113
 
9.0%
o 108
 
8.6%
s 101
 
8.0%
i 79
 
6.3%
r 63
 
5.0%
a 53
 
4.2%
l 53
 
4.2%
d 48
 
3.8%
Other values (25) 328
26.1%
Common
ValueCountFrequency (%)
225
92.2%
8 9
 
3.7%
) 2
 
0.8%
( 2
 
0.8%
, 2
 
0.8%
: 2
 
0.8%
. 1
 
0.4%
4 1
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1500
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
225
15.0%
n 157
 
10.5%
e 153
 
10.2%
t 113
 
7.5%
o 108
 
7.2%
s 101
 
6.7%
i 79
 
5.3%
r 63
 
4.2%
a 53
 
3.5%
l 53
 
3.5%
Other values (33) 395
26.3%

eligibility3
Text

MISSING 

Distinct6
Distinct (%)60.0%
Missing430
Missing (%)97.7%
Memory size14.7 KiB
2023-12-09T22:09:21.960136image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length163
Median length97
Mean length59.9
Min length35

Characters and Unicode

Total characters599
Distinct characters33
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)40.0%

Sample

1st rowOpen only to Queens students or residents
2nd rowOpen only to students whose home language is Spanish
3rd rowOpen only to New York City residents whose home language is Spanish and are proficient in English
4th rowOpen only to Brooklyn students or residents
5th rowOpen only to continuing 8th graders
ValueCountFrequency (%)
open 10
 
9.7%
to 10
 
9.7%
only 10
 
9.7%
residents 8
 
7.8%
students 7
 
6.8%
or 7
 
6.8%
whose 3
 
2.9%
spanish 3
 
2.9%
is 3
 
2.9%
home 3
 
2.9%
Other values (26) 39
37.9%
2023-12-09T22:09:22.339609image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
93
15.5%
e 64
10.7%
n 59
9.8%
o 47
 
7.8%
s 47
 
7.8%
t 42
 
7.0%
i 30
 
5.0%
r 29
 
4.8%
d 21
 
3.5%
l 20
 
3.3%
Other values (23) 147
24.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 475
79.3%
Space Separator 93
 
15.5%
Uppercase Letter 29
 
4.8%
Decimal Number 1
 
0.2%
Other Punctuation 1
 
0.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 64
13.5%
n 59
12.4%
o 47
9.9%
s 47
9.9%
t 42
8.8%
i 30
 
6.3%
r 29
 
6.1%
d 21
 
4.4%
l 20
 
4.2%
y 17
 
3.6%
Other values (11) 99
20.8%
Uppercase Letter
ValueCountFrequency (%)
O 10
34.5%
S 4
 
13.8%
Q 3
 
10.3%
B 3
 
10.3%
C 2
 
6.9%
Y 2
 
6.9%
N 2
 
6.9%
E 2
 
6.9%
U 1
 
3.4%
Space Separator
ValueCountFrequency (%)
93
100.0%
Decimal Number
ValueCountFrequency (%)
8 1
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 504
84.1%
Common 95
 
15.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 64
12.7%
n 59
11.7%
o 47
 
9.3%
s 47
 
9.3%
t 42
 
8.3%
i 30
 
6.0%
r 29
 
5.8%
d 21
 
4.2%
l 20
 
4.0%
y 17
 
3.4%
Other values (20) 128
25.4%
Common
ValueCountFrequency (%)
93
97.9%
8 1
 
1.1%
, 1
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 599
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
93
15.5%
e 64
10.7%
n 59
9.8%
o 47
 
7.8%
s 47
 
7.8%
t 42
 
7.0%
i 30
 
5.0%
r 29
 
4.8%
d 21
 
3.5%
l 20
 
3.3%
Other values (23) 147
24.5%

eligibility4
Text

MISSING 

Distinct4
Distinct (%)57.1%
Missing433
Missing (%)98.4%
Memory size14.4 KiB
2023-12-09T22:09:22.558216image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length97
Median length59
Mean length52.42857143
Min length41

Characters and Unicode

Total characters367
Distinct characters30
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)28.6%

Sample

1st rowOpen only to students whose home language is Haitian Creole
2nd rowOpen only to Brooklyn students or residents
3rd rowOpen only to New York City residents whose home language is Spanish and are proficient in English
4th rowOpen only to Queens students or residents
5th rowOpen only to Queens students or residents
ValueCountFrequency (%)
open 7
11.3%
to 7
11.3%
only 7
11.3%
students 6
 
9.7%
residents 6
 
9.7%
or 5
 
8.1%
brooklyn 3
 
4.8%
home 2
 
3.2%
language 2
 
3.2%
is 2
 
3.2%
Other values (13) 15
24.2%
2023-12-09T22:09:22.891825image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
55
15.0%
e 40
10.9%
n 39
10.6%
o 32
 
8.7%
s 32
 
8.7%
t 28
 
7.6%
r 18
 
4.9%
i 16
 
4.4%
l 14
 
3.8%
d 13
 
3.5%
Other values (20) 80
21.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 293
79.8%
Space Separator 55
 
15.0%
Uppercase Letter 19
 
5.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 40
13.7%
n 39
13.3%
o 32
10.9%
s 32
10.9%
t 28
9.6%
r 18
 
6.1%
i 16
 
5.5%
l 14
 
4.8%
d 13
 
4.4%
y 11
 
3.8%
Other values (10) 50
17.1%
Uppercase Letter
ValueCountFrequency (%)
O 7
36.8%
B 3
15.8%
Q 2
 
10.5%
C 2
 
10.5%
H 1
 
5.3%
N 1
 
5.3%
Y 1
 
5.3%
S 1
 
5.3%
E 1
 
5.3%
Space Separator
ValueCountFrequency (%)
55
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 312
85.0%
Common 55
 
15.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 40
12.8%
n 39
12.5%
o 32
10.3%
s 32
10.3%
t 28
9.0%
r 18
 
5.8%
i 16
 
5.1%
l 14
 
4.5%
d 13
 
4.2%
y 11
 
3.5%
Other values (19) 69
22.1%
Common
ValueCountFrequency (%)
55
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 367
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
55
15.0%
e 40
10.9%
n 39
10.6%
o 32
 
8.7%
s 32
 
8.7%
t 28
 
7.6%
r 18
 
4.9%
i 16
 
4.4%
l 14
 
3.8%
d 13
 
3.5%
Other values (20) 80
21.8%

eligibility5
Text

MISSING 

Distinct2
Distinct (%)50.0%
Missing436
Missing (%)99.1%
Memory size14.1 KiB
2023-12-09T22:09:23.086323image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length43
Median length43
Mean length42.5
Min length41

Characters and Unicode

Total characters170
Distinct characters17
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)25.0%

Sample

1st rowOpen only to Brooklyn students or residents
2nd rowOpen only to Queens students or residents
3rd rowOpen only to Brooklyn students or residents
4th rowOpen only to Brooklyn students or residents
ValueCountFrequency (%)
open 4
14.3%
only 4
14.3%
to 4
14.3%
students 4
14.3%
or 4
14.3%
residents 4
14.3%
brooklyn 3
10.7%
queens 1
 
3.6%
2023-12-09T22:09:23.429930image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
24
14.1%
n 20
11.8%
e 18
10.6%
o 18
10.6%
s 17
10.0%
t 16
9.4%
r 11
6.5%
d 8
 
4.7%
l 7
 
4.1%
y 7
 
4.1%
Other values (7) 24
14.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 138
81.2%
Space Separator 24
 
14.1%
Uppercase Letter 8
 
4.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n 20
14.5%
e 18
13.0%
o 18
13.0%
s 17
12.3%
t 16
11.6%
r 11
8.0%
d 8
 
5.8%
l 7
 
5.1%
y 7
 
5.1%
u 5
 
3.6%
Other values (3) 11
8.0%
Uppercase Letter
ValueCountFrequency (%)
O 4
50.0%
B 3
37.5%
Q 1
 
12.5%
Space Separator
ValueCountFrequency (%)
24
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 146
85.9%
Common 24
 
14.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
n 20
13.7%
e 18
12.3%
o 18
12.3%
s 17
11.6%
t 16
11.0%
r 11
7.5%
d 8
 
5.5%
l 7
 
4.8%
y 7
 
4.8%
u 5
 
3.4%
Other values (6) 19
13.0%
Common
ValueCountFrequency (%)
24
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 170
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
24
14.1%
n 20
11.8%
e 18
10.6%
o 18
10.6%
s 17
10.0%
t 16
9.4%
r 11
6.5%
d 8
 
4.7%
l 7
 
4.1%
y 7
 
4.1%
Other values (7) 24
14.1%

eligibility6
Text

MISSING 

Distinct2
Distinct (%)100.0%
Missing438
Missing (%)99.5%
Memory size14.0 KiB
2023-12-09T22:09:23.625444image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length43
Median length42
Mean length42
Min length41

Characters and Unicode

Total characters84
Distinct characters17
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st rowOpen only to Brooklyn students or residents
2nd rowOpen only to Queens students or residents
ValueCountFrequency (%)
open 2
14.3%
only 2
14.3%
to 2
14.3%
students 2
14.3%
or 2
14.3%
residents 2
14.3%
brooklyn 1
7.1%
queens 1
7.1%
2023-12-09T22:09:23.961410image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
12
14.3%
e 10
11.9%
n 10
11.9%
s 9
10.7%
t 8
9.5%
o 8
9.5%
r 5
6.0%
d 4
 
4.8%
l 3
 
3.6%
y 3
 
3.6%
Other values (7) 12
14.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 68
81.0%
Space Separator 12
 
14.3%
Uppercase Letter 4
 
4.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 10
14.7%
n 10
14.7%
s 9
13.2%
t 8
11.8%
o 8
11.8%
r 5
7.4%
d 4
 
5.9%
l 3
 
4.4%
y 3
 
4.4%
u 3
 
4.4%
Other values (3) 5
7.4%
Uppercase Letter
ValueCountFrequency (%)
O 2
50.0%
B 1
25.0%
Q 1
25.0%
Space Separator
ValueCountFrequency (%)
12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 72
85.7%
Common 12
 
14.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 10
13.9%
n 10
13.9%
s 9
12.5%
t 8
11.1%
o 8
11.1%
r 5
6.9%
d 4
 
5.6%
l 3
 
4.2%
y 3
 
4.2%
u 3
 
4.2%
Other values (6) 9
12.5%
Common
ValueCountFrequency (%)
12
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 84
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
12
14.3%
e 10
11.9%
n 10
11.9%
s 9
10.7%
t 8
9.5%
o 8
9.5%
r 5
6.0%
d 4
 
4.8%
l 3
 
3.6%
y 3
 
3.6%
Other values (7) 12
14.3%

eligibility7
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing439
Missing (%)99.8%
Memory size13.9 KiB
2023-12-09T22:09:24.162328image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length43
Median length43
Mean length43
Min length43

Characters and Unicode

Total characters43
Distinct characters16
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowOpen only to Brooklyn students or residents
ValueCountFrequency (%)
open 1
14.3%
only 1
14.3%
to 1
14.3%
brooklyn 1
14.3%
students 1
14.3%
or 1
14.3%
residents 1
14.3%
2023-12-09T22:09:24.488307image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6
14.0%
n 5
11.6%
o 5
11.6%
e 4
9.3%
t 4
9.3%
s 4
9.3%
r 3
7.0%
l 2
 
4.7%
y 2
 
4.7%
d 2
 
4.7%
Other values (6) 6
14.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 35
81.4%
Space Separator 6
 
14.0%
Uppercase Letter 2
 
4.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n 5
14.3%
o 5
14.3%
e 4
11.4%
t 4
11.4%
s 4
11.4%
r 3
8.6%
l 2
 
5.7%
y 2
 
5.7%
d 2
 
5.7%
p 1
 
2.9%
Other values (3) 3
8.6%
Uppercase Letter
ValueCountFrequency (%)
O 1
50.0%
B 1
50.0%
Space Separator
ValueCountFrequency (%)
6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 37
86.0%
Common 6
 
14.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
n 5
13.5%
o 5
13.5%
e 4
10.8%
t 4
10.8%
s 4
10.8%
r 3
8.1%
l 2
 
5.4%
y 2
 
5.4%
d 2
 
5.4%
O 1
 
2.7%
Other values (5) 5
13.5%
Common
ValueCountFrequency (%)
6
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 43
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6
14.0%
n 5
11.6%
o 5
11.6%
e 4
9.3%
t 4
9.3%
s 4
9.3%
r 3
7.0%
l 2
 
4.7%
y 2
 
4.7%
d 2
 
4.7%
Other values (6) 6
14.0%

eligibility8
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing440
Missing (%)100.0%
Memory size3.6 KiB

eligibility9
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing440
Missing (%)100.0%
Memory size3.6 KiB

eligibility10
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing440
Missing (%)100.0%
Memory size3.6 KiB

auditioninformation1
Text

MISSING 

Distinct18
Distinct (%)100.0%
Missing422
Missing (%)95.9%
Memory size24.5 KiB
2023-12-09T22:09:24.831181image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1953
Median length284
Mean length411
Min length81

Characters and Unicode

Total characters7398
Distinct characters67
Distinct categories10 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique18 ?
Unique (%)100.0%

Sample

1st rowDuring the audition, students will submit for review 10 original drawings or photographs on 18” x 24” poster board that tells a sequential story without words. Images should demonstrate the applicant’s knowledge of visual composition and storytelling. Students will be shown four images and asked to develop an original story that could be the basis for a film. Three questions should be considered while writing: Who are the characters? What problems do they face? What do they do to resolve them?
2nd rowEach applicant will be required to act, sing and dance at this audition. Please prepare the following: Acting: Present a one-minute memorized monologue (comedic or dramatic) from a published play. Singing: Present 32 bars of a memorized Broadway song (age-appropriate) - an accompanist will be provided, so bring sheet music in the appropriate key. Dancing: Be prepared to learn a short theater dance combination - please wear clothing that allows for freedom of movement, as well as jazz shoes or sneakers.
3rd rowAll students applying to the High School of Fashion Industries are required to audition for the school online at www.fashionhighschool.net or in person. The audition includes an admissions examination and submission of a portfolio. Portfolio Requirements: 8-15 pieces of original art work; this art work can be submitted either online on the schoolÂ’s website (www.fashionhighschool.net) or in person at one of the audition dates listed
4th rowAudition Performance, Improvisation Workshop, Theory Diagnostic, Sight Reading, and Instrument Desirability
5th rowPrepare a portfolio of 8-15 pieces of original work. Include examples of observational drawings. Complete up to three drawing assignments at the audition. Check schoolÂ’s website for examples. They may include: the human figure, and drawing from observation or imagination.
ValueCountFrequency (%)
a 47
 
4.1%
and 43
 
3.8%
of 36
 
3.2%
the 31
 
2.7%
to 28
 
2.5%
be 26
 
2.3%
students 23
 
2.0%
will 19
 
1.7%
or 19
 
1.7%
audition 16
 
1.4%
Other values (395) 846
74.6%
2023-12-09T22:09:25.335272image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1116
15.1%
e 632
 
8.5%
o 526
 
7.1%
a 490
 
6.6%
i 464
 
6.3%
t 463
 
6.3%
n 415
 
5.6%
r 394
 
5.3%
s 383
 
5.2%
l 291
 
3.9%
Other values (57) 2224
30.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 5880
79.5%
Space Separator 1116
 
15.1%
Other Punctuation 161
 
2.2%
Uppercase Letter 149
 
2.0%
Decimal Number 32
 
0.4%
Dash Punctuation 23
 
0.3%
Open Punctuation 13
 
0.2%
Close Punctuation 13
 
0.2%
Final Punctuation 10
 
0.1%
Initial Punctuation 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 632
10.7%
o 526
 
8.9%
a 490
 
8.3%
i 464
 
7.9%
t 463
 
7.9%
n 415
 
7.1%
r 394
 
6.7%
s 383
 
6.5%
l 291
 
4.9%
d 265
 
4.5%
Other values (16) 1557
26.5%
Uppercase Letter
ValueCountFrequency (%)
S 21
14.1%
P 20
13.4%
A 19
12.8%
T 13
8.7%
 11
7.4%
B 10
 
6.7%
D 8
 
5.4%
C 8
 
5.4%
I 8
 
5.4%
W 5
 
3.4%
Other values (10) 26
17.4%
Decimal Number
ValueCountFrequency (%)
1 10
31.2%
8 6
18.8%
5 4
 
12.5%
0 4
 
12.5%
2 4
 
12.5%
4 2
 
6.2%
6 1
 
3.1%
3 1
 
3.1%
Other Punctuation
ValueCountFrequency (%)
. 82
50.9%
, 56
34.8%
: 18
 
11.2%
? 3
 
1.9%
; 1
 
0.6%
/ 1
 
0.6%
Final Punctuation
ValueCountFrequency (%)
’ 7
70.0%
” 3
30.0%
Space Separator
ValueCountFrequency (%)
1116
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 23
100.0%
Open Punctuation
ValueCountFrequency (%)
( 13
100.0%
Close Punctuation
ValueCountFrequency (%)
) 13
100.0%
Initial Punctuation
ValueCountFrequency (%)
“ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 6029
81.5%
Common 1369
 
18.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 632
 
10.5%
o 526
 
8.7%
a 490
 
8.1%
i 464
 
7.7%
t 463
 
7.7%
n 415
 
6.9%
r 394
 
6.5%
s 383
 
6.4%
l 291
 
4.8%
d 265
 
4.4%
Other values (36) 1706
28.3%
Common
ValueCountFrequency (%)
1116
81.5%
. 82
 
6.0%
, 56
 
4.1%
- 23
 
1.7%
: 18
 
1.3%
( 13
 
0.9%
) 13
 
0.9%
1 10
 
0.7%
’ 7
 
0.5%
8 6
 
0.4%
Other values (11) 25
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7376
99.7%
None 11
 
0.1%
Punctuation 11
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1116
15.1%
e 632
 
8.6%
o 526
 
7.1%
a 490
 
6.6%
i 464
 
6.3%
t 463
 
6.3%
n 415
 
5.6%
r 394
 
5.3%
s 383
 
5.2%
l 291
 
3.9%
Other values (53) 2202
29.9%
None
ValueCountFrequency (%)
 11
100.0%
Punctuation
ValueCountFrequency (%)
’ 7
63.6%
” 3
27.3%
“ 1
 
9.1%

auditioninformation2
Text

MISSING 

Distinct16
Distinct (%)100.0%
Missing424
Missing (%)96.4%
Memory size19.9 KiB
2023-12-09T22:09:25.714285image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length526
Median length263.5
Mean length286.8125
Min length72

Characters and Unicode

Total characters4589
Distinct characters56
Distinct categories9 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique16 ?
Unique (%)100.0%

Sample

1st rowPresent a portfolio with 10-15 pieces of original work created from observation and from studentÂ’s own imagination, with a diversity of subject matter and use of media, including examples of line, value and color. Student work should be unframed and need not be matted. Three-dimensional work can be shown in photographs. You will also be required to draw from observation and memory, using pencil.
2nd rowPrepare two contrasting monologues (one minute each), for example: dramatic/comedic, classical/contemporary, published/original, or theater/film. Choose characters close to your age or life experience, decide who your characters are talking to and why, and completely memorize both pieces.
3rd rowAll students applying to the High School of Fashion Industries are required to audition for the school online at www.fashionhighschool.net or in person. The audition includes an admissions examination and submission of a portfolio. Portfolio Requirements: 5 original fashion illustrations; these fashion illustrations can be submitted either online on the schoolÂ’s website (www.fashionhighschool.net) or in person at one of the audition dates listed.
4th rowStudents are expected to prepare a one-minute dance solo from any genre.
5th rowPerform two contrasting monologues (one minute each). Perform an on-demand dramatic or movement activity (e.g. impromptu reading from provided script or improvisation). Wear attire that allows free movement.
ValueCountFrequency (%)
and 27
 
3.9%
a 25
 
3.6%
to 20
 
2.9%
of 19
 
2.8%
the 17
 
2.5%
be 15
 
2.2%
audition 14
 
2.0%
or 12
 
1.7%
will 11
 
1.6%
perform 9
 
1.3%
Other values (257) 517
75.4%
2023-12-09T22:09:26.233192image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
670
14.6%
e 377
 
8.2%
o 328
 
7.1%
i 310
 
6.8%
t 305
 
6.6%
a 292
 
6.4%
n 277
 
6.0%
s 242
 
5.3%
r 238
 
5.2%
l 164
 
3.6%
Other values (46) 1386
30.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 3685
80.3%
Space Separator 670
 
14.6%
Other Punctuation 120
 
2.6%
Uppercase Letter 64
 
1.4%
Open Punctuation 13
 
0.3%
Close Punctuation 12
 
0.3%
Dash Punctuation 11
 
0.2%
Decimal Number 11
 
0.2%
Final Punctuation 3
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 377
 
10.2%
o 328
 
8.9%
i 310
 
8.4%
t 305
 
8.3%
a 292
 
7.9%
n 277
 
7.5%
s 242
 
6.6%
r 238
 
6.5%
l 164
 
4.5%
d 143
 
3.9%
Other values (16) 1009
27.4%
Uppercase Letter
ValueCountFrequency (%)
A 13
20.3%
P 11
17.2%
C 6
9.4%
S 5
 
7.8%
I 5
 
7.8%
B 4
 
6.2%
T 4
 
6.2%
Y 4
 
6.2%
R 3
 
4.7%
 3
 
4.7%
Other values (5) 6
9.4%
Other Punctuation
ValueCountFrequency (%)
. 58
48.3%
, 51
42.5%
/ 6
 
5.0%
: 3
 
2.5%
; 1
 
0.8%
' 1
 
0.8%
Decimal Number
ValueCountFrequency (%)
5 4
36.4%
1 4
36.4%
0 2
18.2%
8 1
 
9.1%
Space Separator
ValueCountFrequency (%)
670
100.0%
Open Punctuation
ValueCountFrequency (%)
( 13
100.0%
Close Punctuation
ValueCountFrequency (%)
) 12
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 11
100.0%
Final Punctuation
ValueCountFrequency (%)
’ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 3749
81.7%
Common 840
 
18.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 377
 
10.1%
o 328
 
8.7%
i 310
 
8.3%
t 305
 
8.1%
a 292
 
7.8%
n 277
 
7.4%
s 242
 
6.5%
r 238
 
6.3%
l 164
 
4.4%
d 143
 
3.8%
Other values (31) 1073
28.6%
Common
ValueCountFrequency (%)
670
79.8%
. 58
 
6.9%
, 51
 
6.1%
( 13
 
1.5%
) 12
 
1.4%
- 11
 
1.3%
/ 6
 
0.7%
5 4
 
0.5%
1 4
 
0.5%
: 3
 
0.4%
Other values (5) 8
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4583
99.9%
Punctuation 3
 
0.1%
None 3
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
670
14.6%
e 377
 
8.2%
o 328
 
7.2%
i 310
 
6.8%
t 305
 
6.7%
a 292
 
6.4%
n 277
 
6.0%
s 242
 
5.3%
r 238
 
5.2%
l 164
 
3.6%
Other values (44) 1380
30.1%
Punctuation
ValueCountFrequency (%)
’ 3
100.0%
None
ValueCountFrequency (%)
 3
100.0%

auditioninformation3
Text

MISSING 

Distinct14
Distinct (%)100.0%
Missing426
Missing (%)96.8%
Memory size19.7 KiB
2023-12-09T22:09:26.538634image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length530
Median length327.5
Mean length320.8571429
Min length87

Characters and Unicode

Total characters4492
Distinct characters62
Distinct categories10 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique14 ?
Unique (%)100.0%

Sample

1st rowPerform at least one solo selection and three major scales. Take a sight-reading test and a rhythmic comprehension test in which you are required to tap back rhythmic patterns. Bring your own instrument (except piano, tuba, double bass, percussion instruments, guitar amplifiers); bring 2 copies of audition music.
2nd rowPresent a memorized classical music selection. The song must demonstrate vocal skills and ability. Classical selections can be found in either “Twenty-Four Italian Songs and Arias” or “The Art Song Anthology.” Do not present rock, pop, gospel, country, musical theater, Disney or contemporary music. You must bring sheet music for your song to the audition; an accompanist will be provided. Vocal musicianship (the ability to sing scales, sing a cappella, etc.) will be tested at the audition.
3rd rowAll students applying to the High School of Fashion Industries are required to audition for the school online at www.fashionhighschool.net or in person. The audition includes an admissions examination and submission of a portfolio. Portfolio Requirements: 200-word essay describing a studentÂ’s favorite place to shop and a visual advertisement for this store; this essay and visual advertisement can be submitted either online on the schoolÂ’s website (www.fashionhighschool.net) or in person at one of the audition dates listed.
4th rowPrepare a portfolio of 8-10 pieces of original work (no cartoons). There will be a test that includes drawing from still life and six drawings from imagination.
5th rowInstrumental students will be asked to demonstrate the ability to match pitch, tap rhythms and play various scales and/or exercises, as well as play a prepared selection of their choice.
ValueCountFrequency (%)
a 34
 
4.8%
and 26
 
3.7%
the 22
 
3.1%
to 19
 
2.7%
be 16
 
2.3%
of 14
 
2.0%
in 14
 
2.0%
or 13
 
1.8%
will 13
 
1.8%
audition 11
 
1.6%
Other values (278) 521
74.1%
2023-12-09T22:09:26.964193image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
689
15.3%
e 381
 
8.5%
t 327
 
7.3%
a 323
 
7.2%
i 288
 
6.4%
o 280
 
6.2%
s 267
 
5.9%
n 243
 
5.4%
r 222
 
4.9%
l 191
 
4.3%
Other values (52) 1281
28.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 3566
79.4%
Space Separator 689
 
15.3%
Other Punctuation 106
 
2.4%
Uppercase Letter 78
 
1.7%
Decimal Number 13
 
0.3%
Dash Punctuation 12
 
0.3%
Close Punctuation 11
 
0.2%
Open Punctuation 11
 
0.2%
Final Punctuation 4
 
0.1%
Initial Punctuation 2
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 381
10.7%
t 327
 
9.2%
a 323
 
9.1%
i 288
 
8.1%
o 280
 
7.9%
s 267
 
7.5%
n 243
 
6.8%
r 222
 
6.2%
l 191
 
5.4%
d 146
 
4.1%
Other values (16) 898
25.2%
Uppercase Letter
ValueCountFrequency (%)
P 12
15.4%
A 10
12.8%
S 8
10.3%
T 7
9.0%
 6
 
7.7%
W 5
 
6.4%
I 5
 
6.4%
F 4
 
5.1%
H 3
 
3.8%
M 3
 
3.8%
Other values (8) 15
19.2%
Other Punctuation
ValueCountFrequency (%)
. 54
50.9%
, 40
37.7%
? 5
 
4.7%
; 4
 
3.8%
: 2
 
1.9%
/ 1
 
0.9%
Decimal Number
ValueCountFrequency (%)
0 4
30.8%
2 4
30.8%
5 2
15.4%
8 2
15.4%
1 1
 
7.7%
Final Punctuation
ValueCountFrequency (%)
’ 2
50.0%
” 2
50.0%
Space Separator
ValueCountFrequency (%)
689
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 12
100.0%
Close Punctuation
ValueCountFrequency (%)
) 11
100.0%
Open Punctuation
ValueCountFrequency (%)
( 11
100.0%
Initial Punctuation
ValueCountFrequency (%)
“ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 3644
81.1%
Common 848
 
18.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 381
 
10.5%
t 327
 
9.0%
a 323
 
8.9%
i 288
 
7.9%
o 280
 
7.7%
s 267
 
7.3%
n 243
 
6.7%
r 222
 
6.1%
l 191
 
5.2%
d 146
 
4.0%
Other values (34) 976
26.8%
Common
ValueCountFrequency (%)
689
81.2%
. 54
 
6.4%
, 40
 
4.7%
- 12
 
1.4%
) 11
 
1.3%
( 11
 
1.3%
? 5
 
0.6%
; 4
 
0.5%
0 4
 
0.5%
2 4
 
0.5%
Other values (8) 14
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4480
99.7%
None 6
 
0.1%
Punctuation 6
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
689
15.4%
e 381
 
8.5%
t 327
 
7.3%
a 323
 
7.2%
i 288
 
6.4%
o 280
 
6.2%
s 267
 
6.0%
n 243
 
5.4%
r 222
 
5.0%
l 191
 
4.3%
Other values (48) 1269
28.3%
None
ValueCountFrequency (%)
 6
100.0%
Punctuation
ValueCountFrequency (%)
’ 2
33.3%
“ 2
33.3%
” 2
33.3%

auditioninformation4
Text

MISSING 

Distinct13
Distinct (%)100.0%
Missing427
Missing (%)97.0%
Memory size17.8 KiB
2023-12-09T22:09:27.393739image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length437
Median length234
Mean length230.7692308
Min length115

Characters and Unicode

Total characters3000
Distinct characters57
Distinct categories10 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique13 ?
Unique (%)100.0%

Sample

1st rowPerform the “Star Spangled Banner” (accompaniment will be provided) and one minute of a classical or a standard musical theatre piece. Bring sheet music in your key.
2nd rowParticipate in an Ailey School master class that includes ballet, modern and jazz techniques. Female applicants must wear a leotard, footless or convertible tights and ballet shoes. Males should wear a fitted t-shirt, black leggings or black tights, a dance belt and ballet shoes. No prepared solo is necessary.
3rd rowPerform two contrasting monologues (one minute each). Further details about audition on school website. Wear attire that allows free movement.
4th rowVocal students will be asked to demonstrate the ability to match pitch by singing short melodies which are played on the piano, tap rhythms back to demonstrate the ability to measure time and sing a prepared selection of their choice.
5th rowPerform a 2-3 minute instrumental piece of music. The style of music can be jazz, gospel, contemporary or classical. Applicants should bring their musical instrument to the audition and the sheet music needed for their performance.
ValueCountFrequency (%)
a 19
 
4.1%
the 19
 
4.1%
of 14
 
3.1%
to 12
 
2.6%
and 12
 
2.6%
perform 10
 
2.2%
or 9
 
2.0%
be 8
 
1.7%
music 8
 
1.7%
students 7
 
1.5%
Other values (208) 341
74.3%
2023-12-09T22:09:27.968390image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
446
14.9%
e 257
 
8.6%
t 211
 
7.0%
a 204
 
6.8%
o 204
 
6.8%
i 176
 
5.9%
n 161
 
5.4%
s 160
 
5.3%
r 157
 
5.2%
l 106
 
3.5%
Other values (47) 918
30.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2392
79.7%
Space Separator 446
 
14.9%
Other Punctuation 71
 
2.4%
Uppercase Letter 53
 
1.8%
Close Punctuation 10
 
0.3%
Open Punctuation 10
 
0.3%
Decimal Number 8
 
0.3%
Dash Punctuation 7
 
0.2%
Final Punctuation 2
 
0.1%
Initial Punctuation 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 257
 
10.7%
t 211
 
8.8%
a 204
 
8.5%
o 204
 
8.5%
i 176
 
7.4%
n 161
 
6.7%
s 160
 
6.7%
r 157
 
6.6%
l 106
 
4.4%
m 102
 
4.3%
Other values (16) 654
27.3%
Uppercase Letter
ValueCountFrequency (%)
P 10
18.9%
A 9
17.0%
S 8
15.1%
M 4
 
7.5%
C 4
 
7.5%
F 3
 
5.7%
T 3
 
5.7%
D 3
 
5.7%
 3
 
5.7%
B 2
 
3.8%
Other values (3) 4
 
7.5%
Other Punctuation
ValueCountFrequency (%)
. 44
62.0%
, 22
31.0%
/ 2
 
2.8%
' 1
 
1.4%
: 1
 
1.4%
@ 1
 
1.4%
Decimal Number
ValueCountFrequency (%)
2 3
37.5%
3 2
25.0%
4 1
 
12.5%
1 1
 
12.5%
0 1
 
12.5%
Final Punctuation
ValueCountFrequency (%)
” 1
50.0%
’ 1
50.0%
Space Separator
ValueCountFrequency (%)
446
100.0%
Close Punctuation
ValueCountFrequency (%)
) 10
100.0%
Open Punctuation
ValueCountFrequency (%)
( 10
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%
Initial Punctuation
ValueCountFrequency (%)
“ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2445
81.5%
Common 555
 
18.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 257
 
10.5%
t 211
 
8.6%
a 204
 
8.3%
o 204
 
8.3%
i 176
 
7.2%
n 161
 
6.6%
s 160
 
6.5%
r 157
 
6.4%
l 106
 
4.3%
m 102
 
4.2%
Other values (29) 707
28.9%
Common
ValueCountFrequency (%)
446
80.4%
. 44
 
7.9%
, 22
 
4.0%
) 10
 
1.8%
( 10
 
1.8%
- 7
 
1.3%
2 3
 
0.5%
3 2
 
0.4%
/ 2
 
0.4%
' 1
 
0.2%
Other values (8) 8
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2994
99.8%
None 3
 
0.1%
Punctuation 3
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
446
14.9%
e 257
 
8.6%
t 211
 
7.0%
a 204
 
6.8%
o 204
 
6.8%
i 176
 
5.9%
n 161
 
5.4%
s 160
 
5.3%
r 157
 
5.2%
l 106
 
3.5%
Other values (43) 912
30.5%
None
ValueCountFrequency (%)
 3
100.0%
Punctuation
ValueCountFrequency (%)
” 1
33.3%
“ 1
33.3%
’ 1
33.3%

auditioninformation5
Text

MISSING 

Distinct12
Distinct (%)100.0%
Missing428
Missing (%)97.3%
Memory size17.6 KiB
2023-12-09T22:09:28.306618image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length502
Median length228
Mean length244.0833333
Min length55

Characters and Unicode

Total characters2929
Distinct characters52
Distinct categories9 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique12 ?
Unique (%)100.0%

Sample

1st rowStudents will take an abbreviated ballet class followed by modern and jazz dance combinations. Participants are to audition in appropriate dance attire: leotard, tights and ballet shoes.
2nd rowSelect, study, memorize and perform a 1-3 minute monologue of drama or comedy. Applicants will also be interviewed and asked for a writing sample.
3rd rowVocal Music: Perform a prepared vocal selection. Please provide sheet music for pianist. Instrumental Music: Perform a prepared solo selection and a scale. Bring your own instrument (except piano, double bass, tuba, percussion and guitar amplifiers, which will be provided). For both art forms, the audition includes on-site music tasks (may include singing back melodic patterns, tapping back rhythmic patterns, play selected scales, or completing a sight reading, music theory or improvisation task).
4th rowApplicants will be asked to perform two contrasting monologues (one minute each), and an on-demand dramatic or movement activity (e.g. impromptu reading from provided script or improvisation). Applicants should wear attire that allows free movement.
5th rowPerform a gospel and a classical selection (a capella).
ValueCountFrequency (%)
and 17
 
3.9%
a 14
 
3.2%
to 11
 
2.5%
perform 11
 
2.5%
be 10
 
2.3%
the 10
 
2.3%
or 10
 
2.3%
will 9
 
2.1%
of 8
 
1.9%
applicants 7
 
1.6%
Other values (172) 325
75.2%
2023-12-09T22:09:28.765154image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
420
14.3%
e 254
 
8.7%
a 204
 
7.0%
o 194
 
6.6%
t 191
 
6.5%
i 186
 
6.4%
n 165
 
5.6%
r 164
 
5.6%
s 137
 
4.7%
l 112
 
3.8%
Other values (42) 902
30.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2359
80.5%
Space Separator 420
 
14.3%
Other Punctuation 70
 
2.4%
Uppercase Letter 44
 
1.5%
Open Punctuation 9
 
0.3%
Close Punctuation 9
 
0.3%
Dash Punctuation 8
 
0.3%
Decimal Number 8
 
0.3%
Final Punctuation 2
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 254
 
10.8%
a 204
 
8.6%
o 194
 
8.2%
t 191
 
8.1%
i 186
 
7.9%
n 165
 
7.0%
r 164
 
7.0%
s 137
 
5.8%
l 112
 
4.7%
d 102
 
4.3%
Other values (16) 650
27.6%
Uppercase Letter
ValueCountFrequency (%)
P 9
20.5%
A 7
15.9%
C 5
11.4%
S 5
11.4%
I 4
9.1%
M 3
 
6.8%
W 2
 
4.5%
T 2
 
4.5%
 2
 
4.5%
U 1
 
2.3%
Other values (4) 4
9.1%
Decimal Number
ValueCountFrequency (%)
1 3
37.5%
8 2
25.0%
5 2
25.0%
3 1
 
12.5%
Other Punctuation
ValueCountFrequency (%)
. 45
64.3%
, 21
30.0%
: 4
 
5.7%
Space Separator
ValueCountFrequency (%)
420
100.0%
Open Punctuation
ValueCountFrequency (%)
( 9
100.0%
Close Punctuation
ValueCountFrequency (%)
) 9
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 8
100.0%
Final Punctuation
ValueCountFrequency (%)
’ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2403
82.0%
Common 526
 
18.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 254
 
10.6%
a 204
 
8.5%
o 194
 
8.1%
t 191
 
7.9%
i 186
 
7.7%
n 165
 
6.9%
r 164
 
6.8%
s 137
 
5.7%
l 112
 
4.7%
d 102
 
4.2%
Other values (30) 694
28.9%
Common
ValueCountFrequency (%)
420
79.8%
. 45
 
8.6%
, 21
 
4.0%
( 9
 
1.7%
) 9
 
1.7%
- 8
 
1.5%
: 4
 
0.8%
1 3
 
0.6%
8 2
 
0.4%
’ 2
 
0.4%
Other values (2) 3
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2925
99.9%
Punctuation 2
 
0.1%
None 2
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
420
14.4%
e 254
 
8.7%
a 204
 
7.0%
o 194
 
6.6%
t 191
 
6.5%
i 186
 
6.4%
n 165
 
5.6%
r 164
 
5.6%
s 137
 
4.7%
l 112
 
3.8%
Other values (40) 898
30.7%
Punctuation
ValueCountFrequency (%)
’ 2
100.0%
None
ValueCountFrequency (%)
 2
100.0%

auditioninformation6
Text

MISSING 

Distinct4
Distinct (%)100.0%
Missing436
Missing (%)99.1%
Memory size16.2 KiB
2023-12-09T22:09:29.088900image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length574
Median length373
Mean length362.75
Min length131

Characters and Unicode

Total characters1451
Distinct characters49
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)100.0%

Sample

1st rowPresent two memorized, contrasting, one-minute monologues that must be from published plays – no Internet or original material will be accepted; do a cold reading from selected scenes.
2nd rowYou may audition on more than one instrument. Perform a prepared solo selection. Bring your own instrument(s) (except piano, tuba, double bass, harp, percussion and guitar amplifiers, which are provided by the school). The student must bring a copy of the music they are performing for the adjudicating teacher. The copy will be returned to the student after the audition.Audition includes on-site music tasks (may include singing back melodic patterns, tapping back rhythmic patterns, play selected scales, or completing a sight reading, music theory or improvisation task.
3rd rowApplicants must bring a portfolio of 8-15 pieces of original artwork done in a variety of media. The artwork should be from observation, imagination, and memory, and labeled appropriately. Photographs—not originals—of three-dimensional (3D) works may be included. For the audition, applicants will be given three drawing assignments, including drawing the human figure from observation, drawing a still life from memory, and creating a drawing in color, based on imagination. All drawing materials for auditions will be supplied by the school at the audition.
4th rowArt students must present a current portfolio including requirements which can be found on the Wagner website - www.wagnerhigh.net.
ValueCountFrequency (%)
the 13
 
6.0%
a 9
 
4.1%
be 8
 
3.7%
drawing 5
 
2.3%
from 5
 
2.3%
must 4
 
1.8%
and 4
 
1.8%
will 4
 
1.8%
of 4
 
1.8%
or 3
 
1.4%
Other values (126) 158
72.8%
2023-12-09T22:09:29.529034image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
213
14.7%
e 117
 
8.1%
i 103
 
7.1%
n 94
 
6.5%
t 94
 
6.5%
o 92
 
6.3%
a 89
 
6.1%
r 84
 
5.8%
s 65
 
4.5%
l 50
 
3.4%
Other values (39) 450
31.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1165
80.3%
Space Separator 213
 
14.7%
Other Punctuation 35
 
2.4%
Uppercase Letter 19
 
1.3%
Dash Punctuation 8
 
0.6%
Open Punctuation 4
 
0.3%
Decimal Number 4
 
0.3%
Close Punctuation 3
 
0.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 117
 
10.0%
i 103
 
8.8%
n 94
 
8.1%
t 94
 
8.1%
o 92
 
7.9%
a 89
 
7.6%
r 84
 
7.2%
s 65
 
5.6%
l 50
 
4.3%
d 49
 
4.2%
Other values (16) 328
28.2%
Uppercase Letter
ValueCountFrequency (%)
A 4
21.1%
T 3
15.8%
P 3
15.8%
 3
15.8%
D 1
 
5.3%
W 1
 
5.3%
I 1
 
5.3%
B 1
 
5.3%
Y 1
 
5.3%
F 1
 
5.3%
Decimal Number
ValueCountFrequency (%)
3 1
25.0%
5 1
25.0%
1 1
25.0%
8 1
25.0%
Other Punctuation
ValueCountFrequency (%)
, 19
54.3%
. 15
42.9%
; 1
 
2.9%
Dash Punctuation
ValueCountFrequency (%)
- 5
62.5%
— 2
 
25.0%
– 1
 
12.5%
Space Separator
ValueCountFrequency (%)
213
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1184
81.6%
Common 267
 
18.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 117
 
9.9%
i 103
 
8.7%
n 94
 
7.9%
t 94
 
7.9%
o 92
 
7.8%
a 89
 
7.5%
r 84
 
7.1%
s 65
 
5.5%
l 50
 
4.2%
d 49
 
4.1%
Other values (26) 347
29.3%
Common
ValueCountFrequency (%)
213
79.8%
, 19
 
7.1%
. 15
 
5.6%
- 5
 
1.9%
( 4
 
1.5%
) 3
 
1.1%
— 2
 
0.7%
3 1
 
0.4%
5 1
 
0.4%
1 1
 
0.4%
Other values (3) 3
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1445
99.6%
None 3
 
0.2%
Punctuation 3
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
213
14.7%
e 117
 
8.1%
i 103
 
7.1%
n 94
 
6.5%
t 94
 
6.5%
o 92
 
6.4%
a 89
 
6.2%
r 84
 
5.8%
s 65
 
4.5%
l 50
 
3.5%
Other values (36) 444
30.7%
None
ValueCountFrequency (%)
 3
100.0%
Punctuation
ValueCountFrequency (%)
— 2
66.7%
– 1
33.3%

auditioninformation7
Text

MISSING 

Distinct2
Distinct (%)100.0%
Missing438
Missing (%)99.5%
Memory size14.3 KiB
2023-12-09T22:09:29.799996image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length207
Median length181.5
Mean length181.5
Min length156

Characters and Unicode

Total characters363
Distinct characters33
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st rowPerform two contrasting monologues (one minute each). Perform an on-demand dramatic or movement activity (e.g. impromptu reading from provided script or improvisation). Wear attire that allows free movement.
2nd rowTheater students must perform a brief audition, including a short memorized monologue. Requirements can be found on the Wagner website - www.wagnerhigh.net.
ValueCountFrequency (%)
perform 3
 
6.0%
a 2
 
4.0%
or 2
 
4.0%
movement 2
 
4.0%
theater 1
 
2.0%
impromptu 1
 
2.0%
each 1
 
2.0%
an 1
 
2.0%
on-demand 1
 
2.0%
dramatic 1
 
2.0%
Other values (35) 35
70.0%
2023-12-09T22:09:30.189374image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
48
13.2%
e 36
 
9.9%
o 28
 
7.7%
t 26
 
7.2%
r 26
 
7.2%
n 24
 
6.6%
i 22
 
6.1%
a 20
 
5.5%
m 20
 
5.5%
s 11
 
3.0%
Other values (23) 102
28.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 293
80.7%
Space Separator 48
 
13.2%
Other Punctuation 10
 
2.8%
Uppercase Letter 6
 
1.7%
Dash Punctuation 2
 
0.6%
Close Punctuation 2
 
0.6%
Open Punctuation 2
 
0.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 36
12.3%
o 28
9.6%
t 26
 
8.9%
r 26
 
8.9%
n 24
 
8.2%
i 22
 
7.5%
a 20
 
6.8%
m 20
 
6.8%
s 11
 
3.8%
d 11
 
3.8%
Other values (13) 69
23.5%
Uppercase Letter
ValueCountFrequency (%)
P 2
33.3%
W 2
33.3%
T 1
16.7%
R 1
16.7%
Other Punctuation
ValueCountFrequency (%)
. 9
90.0%
, 1
 
10.0%
Space Separator
ValueCountFrequency (%)
48
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 299
82.4%
Common 64
 
17.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 36
12.0%
o 28
 
9.4%
t 26
 
8.7%
r 26
 
8.7%
n 24
 
8.0%
i 22
 
7.4%
a 20
 
6.7%
m 20
 
6.7%
s 11
 
3.7%
d 11
 
3.7%
Other values (17) 75
25.1%
Common
ValueCountFrequency (%)
48
75.0%
. 9
 
14.1%
- 2
 
3.1%
) 2
 
3.1%
( 2
 
3.1%
, 1
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 363
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
48
13.2%
e 36
 
9.9%
o 28
 
7.7%
t 26
 
7.2%
r 26
 
7.2%
n 24
 
6.6%
i 22
 
6.1%
a 20
 
5.5%
m 20
 
5.5%
s 11
 
3.0%
Other values (23) 102
28.1%

auditioninformation8
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing440
Missing (%)100.0%
Memory size3.6 KiB

auditioninformation9
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing440
Missing (%)100.0%
Memory size3.6 KiB

auditioninformation10
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing440
Missing (%)100.0%
Memory size3.6 KiB

common_audition1
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)10.0%
Missing430
Missing (%)97.7%
Memory size14.1 KiB
2023-12-09T22:09:30.310197image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters10
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1
ValueCountFrequency (%)
1 10
100.0%
2023-12-09T22:09:30.529003image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 10
100.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 10
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 10
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 10
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 10
100.0%

common_audition2
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)10.0%
Missing430
Missing (%)97.7%
Memory size14.1 KiB
2023-12-09T22:09:30.640367image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters10
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1
ValueCountFrequency (%)
1 10
100.0%
2023-12-09T22:09:30.861092image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 10
100.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 10
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 10
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 10
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 10
100.0%

common_audition3
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)12.5%
Missing432
Missing (%)98.2%
Memory size14.1 KiB
2023-12-09T22:09:30.965413image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters8
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1
ValueCountFrequency (%)
1 8
100.0%
2023-12-09T22:09:31.177806image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 8
100.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 8
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 8
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 8
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 8
100.0%

common_audition4
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)16.7%
Missing434
Missing (%)98.6%
Memory size14.0 KiB
2023-12-09T22:09:31.279298image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters6
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1
ValueCountFrequency (%)
1 6
100.0%
2023-12-09T22:09:31.505324image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 6
100.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 6
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 6
100.0%

common_audition5
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)12.5%
Missing432
Missing (%)98.2%
Memory size14.1 KiB
2023-12-09T22:09:31.609031image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters8
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1
ValueCountFrequency (%)
1 8
100.0%
2023-12-09T22:09:31.819383image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 8
100.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 8
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 8
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 8
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 8
100.0%

common_audition6
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)50.0%
Missing438
Missing (%)99.5%
Memory size13.9 KiB
2023-12-09T22:09:31.925904image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters2
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
ValueCountFrequency (%)
1 2
100.0%
2023-12-09T22:09:32.146589image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 2
100.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 2
100.0%

common_audition7
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing439
Missing (%)99.8%
Memory size13.9 KiB
2023-12-09T22:09:32.254186image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row1
ValueCountFrequency (%)
1 1
100.0%
2023-12-09T22:09:32.480647image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 1
100.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 1
100.0%

common_audition8
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing440
Missing (%)100.0%
Memory size3.6 KiB

common_audition9
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing440
Missing (%)100.0%
Memory size3.6 KiB

common_audition10
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing440
Missing (%)100.0%
Memory size3.6 KiB

grade9geapplicantsperseat1
Text

MISSING 

Distinct39
Distinct (%)9.3%
Missing20
Missing (%)4.5%
Memory size24.7 KiB
2023-12-09T22:09:32.689363image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.29047619
Min length1

Characters and Unicode

Total characters542
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10 ?
Unique (%)2.4%

Sample

1st row19
2nd row4
3rd row3
4th row3
5th row5
ValueCountFrequency (%)
4 59
14.0%
3 52
12.4%
2 47
11.2%
5 45
10.7%
7 28
 
6.7%
6 26
 
6.2%
9 19
 
4.5%
11 15
 
3.6%
8 13
 
3.1%
10 12
 
2.9%
Other values (29) 104
24.8%
2023-12-09T22:09:33.032932image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 113
20.8%
2 82
15.1%
4 77
14.2%
3 71
13.1%
5 62
11.4%
6 39
 
7.2%
7 34
 
6.3%
9 24
 
4.4%
8 22
 
4.1%
0 18
 
3.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 542
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 113
20.8%
2 82
15.1%
4 77
14.2%
3 71
13.1%
5 62
11.4%
6 39
 
7.2%
7 34
 
6.3%
9 24
 
4.4%
8 22
 
4.1%
0 18
 
3.3%

Most occurring scripts

ValueCountFrequency (%)
Common 542
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 113
20.8%
2 82
15.1%
4 77
14.2%
3 71
13.1%
5 62
11.4%
6 39
 
7.2%
7 34
 
6.3%
9 24
 
4.4%
8 22
 
4.1%
0 18
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 542
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 113
20.8%
2 82
15.1%
4 77
14.2%
3 71
13.1%
5 62
11.4%
6 39
 
7.2%
7 34
 
6.3%
9 24
 
4.4%
8 22
 
4.1%
0 18
 
3.3%

grade9geapplicantsperseat2
Text

MISSING 

Distinct23
Distinct (%)20.5%
Missing328
Missing (%)74.5%
Memory size16.7 KiB
2023-12-09T22:09:33.236613image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.276785714
Min length1

Characters and Unicode

Total characters143
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7 ?
Unique (%)6.2%

Sample

1st row4
2nd row11
3rd row13
4th row7
5th row14
ValueCountFrequency (%)
2 13
11.6%
3 13
11.6%
1 11
9.8%
4 11
9.8%
5 11
9.8%
7 10
8.9%
6 6
 
5.4%
9 5
 
4.5%
13 5
 
4.5%
12 4
 
3.6%
Other values (13) 23
20.5%
2023-12-09T22:09:33.556680image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 36
25.2%
2 25
17.5%
3 19
13.3%
4 17
11.9%
5 15
10.5%
7 10
 
7.0%
0 8
 
5.6%
6 6
 
4.2%
9 6
 
4.2%
8 1
 
0.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 143
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 36
25.2%
2 25
17.5%
3 19
13.3%
4 17
11.9%
5 15
10.5%
7 10
 
7.0%
0 8
 
5.6%
6 6
 
4.2%
9 6
 
4.2%
8 1
 
0.7%

Most occurring scripts

ValueCountFrequency (%)
Common 143
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 36
25.2%
2 25
17.5%
3 19
13.3%
4 17
11.9%
5 15
10.5%
7 10
 
7.0%
0 8
 
5.6%
6 6
 
4.2%
9 6
 
4.2%
8 1
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 143
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 36
25.2%
2 25
17.5%
3 19
13.3%
4 17
11.9%
5 15
10.5%
7 10
 
7.0%
0 8
 
5.6%
6 6
 
4.2%
9 6
 
4.2%
8 1
 
0.7%

grade9geapplicantsperseat3
Text

MISSING 

Distinct22
Distinct (%)34.9%
Missing377
Missing (%)85.7%
Memory size15.5 KiB
2023-12-09T22:09:33.736099image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.301587302
Min length1

Characters and Unicode

Total characters82
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8 ?
Unique (%)12.7%

Sample

1st row12
2nd row8
3rd row8
4th row4
5th row3
ValueCountFrequency (%)
3 13
20.6%
4 11
17.5%
7 4
 
6.3%
5 4
 
6.3%
8 3
 
4.8%
18 3
 
4.8%
1 3
 
4.8%
2 2
 
3.2%
6 2
 
3.2%
29 2
 
3.2%
Other values (12) 16
25.4%
2023-12-09T22:09:34.033746image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 18
22.0%
3 15
18.3%
4 13
15.9%
2 8
9.8%
8 7
 
8.5%
7 6
 
7.3%
5 6
 
7.3%
9 4
 
4.9%
6 3
 
3.7%
0 2
 
2.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 82
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 18
22.0%
3 15
18.3%
4 13
15.9%
2 8
9.8%
8 7
 
8.5%
7 6
 
7.3%
5 6
 
7.3%
9 4
 
4.9%
6 3
 
3.7%
0 2
 
2.4%

Most occurring scripts

ValueCountFrequency (%)
Common 82
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 18
22.0%
3 15
18.3%
4 13
15.9%
2 8
9.8%
8 7
 
8.5%
7 6
 
7.3%
5 6
 
7.3%
9 4
 
4.9%
6 3
 
3.7%
0 2
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 82
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 18
22.0%
3 15
18.3%
4 13
15.9%
2 8
9.8%
8 7
 
8.5%
7 6
 
7.3%
5 6
 
7.3%
9 4
 
4.9%
6 3
 
3.7%
0 2
 
2.4%

grade9geapplicantsperseat4
Text

MISSING 

Distinct17
Distinct (%)37.0%
Missing394
Missing (%)89.5%
Memory size15.1 KiB
2023-12-09T22:09:34.211380image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.260869565
Min length1

Characters and Unicode

Total characters58
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7 ?
Unique (%)15.2%

Sample

1st row22
2nd row10
3rd row4
4th row2
5th row2
ValueCountFrequency (%)
2 7
15.2%
3 7
15.2%
4 6
13.0%
9 4
8.7%
6 3
6.5%
5 3
6.5%
11 3
6.5%
21 2
 
4.3%
8 2
 
4.3%
1 2
 
4.3%
Other values (7) 7
15.2%
2023-12-09T22:09:34.509442image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 14
24.1%
2 11
19.0%
3 10
17.2%
4 7
12.1%
9 4
 
6.9%
6 4
 
6.9%
5 3
 
5.2%
8 3
 
5.2%
0 1
 
1.7%
7 1
 
1.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 58
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 14
24.1%
2 11
19.0%
3 10
17.2%
4 7
12.1%
9 4
 
6.9%
6 4
 
6.9%
5 3
 
5.2%
8 3
 
5.2%
0 1
 
1.7%
7 1
 
1.7%

Most occurring scripts

ValueCountFrequency (%)
Common 58
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 14
24.1%
2 11
19.0%
3 10
17.2%
4 7
12.1%
9 4
 
6.9%
6 4
 
6.9%
5 3
 
5.2%
8 3
 
5.2%
0 1
 
1.7%
7 1
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 58
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 14
24.1%
2 11
19.0%
3 10
17.2%
4 7
12.1%
9 4
 
6.9%
6 4
 
6.9%
5 3
 
5.2%
8 3
 
5.2%
0 1
 
1.7%
7 1
 
1.7%

grade9geapplicantsperseat5
Text

MISSING 

Distinct12
Distinct (%)38.7%
Missing409
Missing (%)93.0%
Memory size14.7 KiB
2023-12-09T22:09:34.661060image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.129032258
Min length1

Characters and Unicode

Total characters35
Distinct characters9
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)16.1%

Sample

1st row20
2nd row4
3rd row3
4th row2
5th row6
ValueCountFrequency (%)
3 7
22.6%
2 5
16.1%
4 5
16.1%
8 3
9.7%
9 2
 
6.5%
7 2
 
6.5%
6 2
 
6.5%
37 1
 
3.2%
20 1
 
3.2%
1 1
 
3.2%
Other values (2) 2
 
6.5%
2023-12-09T22:09:34.933120image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 9
25.7%
2 7
20.0%
4 5
14.3%
8 3
 
8.6%
7 3
 
8.6%
9 2
 
5.7%
6 2
 
5.7%
0 2
 
5.7%
1 2
 
5.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 35
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 9
25.7%
2 7
20.0%
4 5
14.3%
8 3
 
8.6%
7 3
 
8.6%
9 2
 
5.7%
6 2
 
5.7%
0 2
 
5.7%
1 2
 
5.7%

Most occurring scripts

ValueCountFrequency (%)
Common 35
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 9
25.7%
2 7
20.0%
4 5
14.3%
8 3
 
8.6%
7 3
 
8.6%
9 2
 
5.7%
6 2
 
5.7%
0 2
 
5.7%
1 2
 
5.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 35
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 9
25.7%
2 7
20.0%
4 5
14.3%
8 3
 
8.6%
7 3
 
8.6%
9 2
 
5.7%
6 2
 
5.7%
0 2
 
5.7%
1 2
 
5.7%

grade9geapplicantsperseat6
Text

MISSING 

Distinct13
Distinct (%)72.2%
Missing422
Missing (%)95.9%
Memory size14.3 KiB
2023-12-09T22:09:35.097783image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.388888889
Min length1

Characters and Unicode

Total characters25
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9 ?
Unique (%)50.0%

Sample

1st row19
2nd row4
3rd row8
4th row12
5th row3
ValueCountFrequency (%)
3 3
16.7%
23 2
11.1%
4 2
11.1%
6 2
11.1%
37 1
 
5.6%
19 1
 
5.6%
1 1
 
5.6%
8 1
 
5.6%
12 1
 
5.6%
10 1
 
5.6%
Other values (3) 3
16.7%
2023-12-09T22:09:35.378005image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 6
24.0%
2 4
16.0%
1 4
16.0%
4 2
 
8.0%
6 2
 
8.0%
7 2
 
8.0%
8 2
 
8.0%
9 1
 
4.0%
0 1
 
4.0%
5 1
 
4.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 25
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 6
24.0%
2 4
16.0%
1 4
16.0%
4 2
 
8.0%
6 2
 
8.0%
7 2
 
8.0%
8 2
 
8.0%
9 1
 
4.0%
0 1
 
4.0%
5 1
 
4.0%

Most occurring scripts

ValueCountFrequency (%)
Common 25
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 6
24.0%
2 4
16.0%
1 4
16.0%
4 2
 
8.0%
6 2
 
8.0%
7 2
 
8.0%
8 2
 
8.0%
9 1
 
4.0%
0 1
 
4.0%
5 1
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 25
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 6
24.0%
2 4
16.0%
1 4
16.0%
4 2
 
8.0%
6 2
 
8.0%
7 2
 
8.0%
8 2
 
8.0%
9 1
 
4.0%
0 1
 
4.0%
5 1
 
4.0%

grade9geapplicantsperseat7
Text

MISSING 

Distinct8
Distinct (%)72.7%
Missing429
Missing (%)97.5%
Memory size14.2 KiB
2023-12-09T22:09:35.545957image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.272727273
Min length1

Characters and Unicode

Total characters14
Distinct characters6
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)45.5%

Sample

1st row8
2nd row5
3rd row5
4th row1
5th row11
ValueCountFrequency (%)
8 2
18.2%
11 2
18.2%
5 2
18.2%
2 1
9.1%
1 1
9.1%
21 1
9.1%
4 1
9.1%
6 1
9.1%
2023-12-09T22:09:35.854521image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 6
42.9%
8 2
 
14.3%
5 2
 
14.3%
2 2
 
14.3%
4 1
 
7.1%
6 1
 
7.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 14
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 6
42.9%
8 2
 
14.3%
5 2
 
14.3%
2 2
 
14.3%
4 1
 
7.1%
6 1
 
7.1%

Most occurring scripts

ValueCountFrequency (%)
Common 14
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 6
42.9%
8 2
 
14.3%
5 2
 
14.3%
2 2
 
14.3%
4 1
 
7.1%
6 1
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 14
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 6
42.9%
8 2
 
14.3%
5 2
 
14.3%
2 2
 
14.3%
4 1
 
7.1%
6 1
 
7.1%

grade9geapplicantsperseat8
Text

MISSING 

Distinct2
Distinct (%)100.0%
Missing438
Missing (%)99.5%
Memory size13.9 KiB
2023-12-09T22:09:35.983747image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters2
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st row2
2nd row9
ValueCountFrequency (%)
2 1
50.0%
9 1
50.0%
2023-12-09T22:09:36.199792image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 1
50.0%
9 1
50.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 1
50.0%
9 1
50.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 1
50.0%
9 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 1
50.0%
9 1
50.0%

grade9geapplicantsperseat9
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing439
Missing (%)99.8%
Memory size13.9 KiB
2023-12-09T22:09:36.302614image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row3
ValueCountFrequency (%)
3 1
100.0%
2023-12-09T22:09:36.515860image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 1
100.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 1
100.0%

grade9geapplicantsperseat10
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing440
Missing (%)100.0%
Memory size3.6 KiB

grade9swdapplicantsperseat1
Text

MISSING 

Distinct22
Distinct (%)5.2%
Missing20
Missing (%)4.5%
Memory size24.6 KiB
2023-12-09T22:09:36.692517image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.188095238
Min length1

Characters and Unicode

Total characters499
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st row9
2nd row2
3rd row3
4th row4
5th row5
ValueCountFrequency (%)
3 57
13.6%
4 50
11.9%
5 49
11.7%
6 40
9.5%
2 35
8.3%
7 35
8.3%
9 31
7.4%
8 30
7.1%
11 15
 
3.6%
10 14
 
3.3%
Other values (12) 64
15.2%
2023-12-09T22:09:36.994959image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 103
20.6%
3 66
13.2%
4 57
11.4%
5 52
10.4%
6 47
9.4%
2 47
9.4%
7 41
 
8.2%
9 39
 
7.8%
8 30
 
6.0%
0 17
 
3.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 499
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 103
20.6%
3 66
13.2%
4 57
11.4%
5 52
10.4%
6 47
9.4%
2 47
9.4%
7 41
 
8.2%
9 39
 
7.8%
8 30
 
6.0%
0 17
 
3.4%

Most occurring scripts

ValueCountFrequency (%)
Common 499
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 103
20.6%
3 66
13.2%
4 57
11.4%
5 52
10.4%
6 47
9.4%
2 47
9.4%
7 41
 
8.2%
9 39
 
7.8%
8 30
 
6.0%
0 17
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 499
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 103
20.6%
3 66
13.2%
4 57
11.4%
5 52
10.4%
6 47
9.4%
2 47
9.4%
7 41
 
8.2%
9 39
 
7.8%
8 30
 
6.0%
0 17
 
3.4%

grade9swdapplicantsperseat2
Text

MISSING 

Distinct18
Distinct (%)16.2%
Missing329
Missing (%)74.8%
Memory size16.7 KiB
2023-12-09T22:09:37.158618image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.144144144
Min length1

Characters and Unicode

Total characters127
Distinct characters9
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)5.4%

Sample

1st row3
2nd row9
3rd row4
4th row11
5th row7
ValueCountFrequency (%)
2 20
18.0%
3 15
13.5%
4 14
12.6%
1 11
9.9%
5 10
9.0%
9 9
8.1%
6 8
 
7.2%
12 6
 
5.4%
7 5
 
4.5%
8 3
 
2.7%
Other values (8) 10
9.0%
2023-12-09T22:09:37.438612image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 28
22.0%
1 25
19.7%
3 17
13.4%
4 14
11.0%
5 13
10.2%
9 12
9.4%
6 9
 
7.1%
7 6
 
4.7%
8 3
 
2.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 127
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 28
22.0%
1 25
19.7%
3 17
13.4%
4 14
11.0%
5 13
10.2%
9 12
9.4%
6 9
 
7.1%
7 6
 
4.7%
8 3
 
2.4%

Most occurring scripts

ValueCountFrequency (%)
Common 127
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 28
22.0%
1 25
19.7%
3 17
13.4%
4 14
11.0%
5 13
10.2%
9 12
9.4%
6 9
 
7.1%
7 6
 
4.7%
8 3
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 127
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 28
22.0%
1 25
19.7%
3 17
13.4%
4 14
11.0%
5 13
10.2%
9 12
9.4%
6 9
 
7.1%
7 6
 
4.7%
8 3
 
2.4%

grade9swdapplicantsperseat3
Text

MISSING 

Distinct16
Distinct (%)26.2%
Missing379
Missing (%)86.1%
Memory size15.4 KiB
2023-12-09T22:09:37.602077image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.163934426
Min length1

Characters and Unicode

Total characters71
Distinct characters9
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)8.2%

Sample

1st row8
2nd row6
3rd row11
4th row5
5th row3
ValueCountFrequency (%)
4 10
16.4%
5 7
11.5%
3 7
11.5%
2 6
9.8%
7 5
8.2%
1 5
8.2%
8 4
 
6.6%
6 4
 
6.6%
9 3
 
4.9%
11 3
 
4.9%
Other values (6) 7
11.5%
2023-12-09T22:09:37.881897image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 15
21.1%
4 12
16.9%
5 9
12.7%
3 9
12.7%
2 7
9.9%
7 6
 
8.5%
8 5
 
7.0%
6 5
 
7.0%
9 3
 
4.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 71
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 15
21.1%
4 12
16.9%
5 9
12.7%
3 9
12.7%
2 7
9.9%
7 6
 
8.5%
8 5
 
7.0%
6 5
 
7.0%
9 3
 
4.2%

Most occurring scripts

ValueCountFrequency (%)
Common 71
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 15
21.1%
4 12
16.9%
5 9
12.7%
3 9
12.7%
2 7
9.9%
7 6
 
8.5%
8 5
 
7.0%
6 5
 
7.0%
9 3
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 71
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 15
21.1%
4 12
16.9%
5 9
12.7%
3 9
12.7%
2 7
9.9%
7 6
 
8.5%
8 5
 
7.0%
6 5
 
7.0%
9 3
 
4.2%

grade9swdapplicantsperseat4
Text

MISSING 

Distinct13
Distinct (%)28.9%
Missing395
Missing (%)89.8%
Memory size15.0 KiB
2023-12-09T22:09:38.039906image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.088888889
Min length1

Characters and Unicode

Total characters49
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)11.1%

Sample

1st row4
2nd row3
3rd row4
4th row3
5th row1
ValueCountFrequency (%)
3 9
20.0%
6 8
17.8%
2 6
13.3%
4 6
13.3%
1 4
8.9%
5 3
 
6.7%
8 2
 
4.4%
9 2
 
4.4%
26 1
 
2.2%
40 1
 
2.2%
Other values (3) 3
 
6.7%
2023-12-09T22:09:38.314746image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 10
20.4%
6 9
18.4%
2 8
16.3%
4 7
14.3%
1 6
12.2%
5 3
 
6.1%
8 2
 
4.1%
9 2
 
4.1%
0 1
 
2.0%
7 1
 
2.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 49
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 10
20.4%
6 9
18.4%
2 8
16.3%
4 7
14.3%
1 6
12.2%
5 3
 
6.1%
8 2
 
4.1%
9 2
 
4.1%
0 1
 
2.0%
7 1
 
2.0%

Most occurring scripts

ValueCountFrequency (%)
Common 49
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 10
20.4%
6 9
18.4%
2 8
16.3%
4 7
14.3%
1 6
12.2%
5 3
 
6.1%
8 2
 
4.1%
9 2
 
4.1%
0 1
 
2.0%
7 1
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 49
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 10
20.4%
6 9
18.4%
2 8
16.3%
4 7
14.3%
1 6
12.2%
5 3
 
6.1%
8 2
 
4.1%
9 2
 
4.1%
0 1
 
2.0%
7 1
 
2.0%

grade9swdapplicantsperseat5
Text

MISSING 

Distinct11
Distinct (%)35.5%
Missing409
Missing (%)93.0%
Memory size14.7 KiB
2023-12-09T22:09:38.472227image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.096774194
Min length1

Characters and Unicode

Total characters34
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)16.1%

Sample

1st row14
2nd row5
3rd row3
4th row2
5th row4
ValueCountFrequency (%)
3 6
19.4%
5 5
16.1%
2 4
12.9%
8 4
12.9%
4 4
12.9%
6 3
9.7%
19 1
 
3.2%
1 1
 
3.2%
14 1
 
3.2%
10 1
 
3.2%
2023-12-09T22:09:38.745278image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 6
17.6%
5 5
14.7%
4 5
14.7%
2 4
11.8%
8 4
11.8%
1 4
11.8%
6 3
8.8%
9 1
 
2.9%
0 1
 
2.9%
7 1
 
2.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 34
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 6
17.6%
5 5
14.7%
4 5
14.7%
2 4
11.8%
8 4
11.8%
1 4
11.8%
6 3
8.8%
9 1
 
2.9%
0 1
 
2.9%
7 1
 
2.9%

Most occurring scripts

ValueCountFrequency (%)
Common 34
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 6
17.6%
5 5
14.7%
4 5
14.7%
2 4
11.8%
8 4
11.8%
1 4
11.8%
6 3
8.8%
9 1
 
2.9%
0 1
 
2.9%
7 1
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 34
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 6
17.6%
5 5
14.7%
4 5
14.7%
2 4
11.8%
8 4
11.8%
1 4
11.8%
6 3
8.8%
9 1
 
2.9%
0 1
 
2.9%
7 1
 
2.9%

grade9swdapplicantsperseat6
Text

MISSING 

Distinct11
Distinct (%)61.1%
Missing422
Missing (%)95.9%
Memory size14.3 KiB
2023-12-09T22:09:38.906566image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.277777778
Min length1

Characters and Unicode

Total characters23
Distinct characters9
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)33.3%

Sample

1st row14
2nd row4
3rd row9
4th row2
5th row5
ValueCountFrequency (%)
2 3
16.7%
5 3
16.7%
16 2
11.1%
4 2
11.1%
6 2
11.1%
28 1
 
5.6%
14 1
 
5.6%
21 1
 
5.6%
3 1
 
5.6%
9 1
 
5.6%
2023-12-09T22:09:39.197047image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 5
21.7%
1 4
17.4%
6 4
17.4%
5 3
13.0%
4 3
13.0%
8 1
 
4.3%
3 1
 
4.3%
9 1
 
4.3%
7 1
 
4.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 23
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 5
21.7%
1 4
17.4%
6 4
17.4%
5 3
13.0%
4 3
13.0%
8 1
 
4.3%
3 1
 
4.3%
9 1
 
4.3%
7 1
 
4.3%

Most occurring scripts

ValueCountFrequency (%)
Common 23
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 5
21.7%
1 4
17.4%
6 4
17.4%
5 3
13.0%
4 3
13.0%
8 1
 
4.3%
3 1
 
4.3%
9 1
 
4.3%
7 1
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 23
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 5
21.7%
1 4
17.4%
6 4
17.4%
5 3
13.0%
4 3
13.0%
8 1
 
4.3%
3 1
 
4.3%
9 1
 
4.3%
7 1
 
4.3%

grade9swdapplicantsperseat7
Text

MISSING 

Distinct7
Distinct (%)63.6%
Missing429
Missing (%)97.5%
Memory size14.2 KiB
2023-12-09T22:09:39.344459image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.090909091
Min length1

Characters and Unicode

Total characters12
Distinct characters6
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)36.4%

Sample

1st row8
2nd row7
3rd row5
4th row2
5th row5
ValueCountFrequency (%)
5 3
27.3%
1 2
18.2%
4 2
18.2%
2 1
 
9.1%
8 1
 
9.1%
21 1
 
9.1%
7 1
 
9.1%
2023-12-09T22:09:39.608815image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 3
25.0%
1 3
25.0%
4 2
16.7%
2 2
16.7%
8 1
 
8.3%
7 1
 
8.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 12
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 3
25.0%
1 3
25.0%
4 2
16.7%
2 2
16.7%
8 1
 
8.3%
7 1
 
8.3%

Most occurring scripts

ValueCountFrequency (%)
Common 12
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 3
25.0%
1 3
25.0%
4 2
16.7%
2 2
16.7%
8 1
 
8.3%
7 1
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 12
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 3
25.0%
1 3
25.0%
4 2
16.7%
2 2
16.7%
8 1
 
8.3%
7 1
 
8.3%

grade9swdapplicantsperseat8
Text

MISSING 

Distinct2
Distinct (%)100.0%
Missing438
Missing (%)99.5%
Memory size13.9 KiB
2023-12-09T22:09:39.722741image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters2
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st row1
2nd row6
ValueCountFrequency (%)
1 1
50.0%
6 1
50.0%
2023-12-09T22:09:39.937685image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 1
50.0%
6 1
50.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 1
50.0%
6 1
50.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 1
50.0%
6 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 1
50.0%
6 1
50.0%

grade9swdapplicantsperseat9
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing439
Missing (%)99.8%
Memory size13.9 KiB
2023-12-09T22:09:40.041562image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row5
ValueCountFrequency (%)
5 1
100.0%
2023-12-09T22:09:40.258420image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 1
100.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 1
100.0%

grade9swdapplicantsperseat10
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing440
Missing (%)100.0%
Memory size3.6 KiB

primary_address_line_1
Text

Distinct262
Distinct (%)59.5%
Missing0
Missing (%)0.0%
Memory size32.9 KiB
2023-12-09T22:09:40.620420image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length30
Median length26
Mean length19.28636364
Min length11

Characters and Unicode

Total characters8486
Distinct characters60
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique181 ?
Unique (%)41.1%

Sample

1st row10 East 15th Street
2nd row2865 West 19th Street
3rd row456 White Plains Road
4th row883 Classon Avenue
5th row121-10 Rockaway Boulevard
ValueCountFrequency (%)
avenue 188
 
12.8%
street 166
 
11.3%
east 56
 
3.8%
west 48
 
3.3%
road 27
 
1.8%
boulevard 14
 
0.9%
place 11
 
0.7%
parkway 9
 
0.6%
irving 9
 
0.6%
100 9
 
0.6%
Other values (464) 937
63.6%
2023-12-09T22:09:41.143924image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1034
 
12.2%
e 983
 
11.6%
t 688
 
8.1%
n 415
 
4.9%
r 365
 
4.3%
0 354
 
4.2%
1 340
 
4.0%
a 330
 
3.9%
u 254
 
3.0%
o 239
 
2.8%
Other values (50) 3484
41.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 4658
54.9%
Decimal Number 1804
 
21.3%
Space Separator 1034
 
12.2%
Uppercase Letter 901
 
10.6%
Dash Punctuation 82
 
1.0%
Other Punctuation 7
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 983
21.1%
t 688
14.8%
n 415
8.9%
r 365
 
7.8%
a 330
 
7.1%
u 254
 
5.5%
o 239
 
5.1%
v 239
 
5.1%
s 231
 
5.0%
h 175
 
3.8%
Other values (13) 739
15.9%
Uppercase Letter
ValueCountFrequency (%)
A 218
24.2%
S 193
21.4%
E 67
 
7.4%
B 67
 
7.4%
W 55
 
6.1%
R 41
 
4.6%
P 37
 
4.1%
G 28
 
3.1%
T 27
 
3.0%
F 26
 
2.9%
Other values (13) 142
15.8%
Decimal Number
ValueCountFrequency (%)
0 354
19.6%
1 340
18.8%
2 206
11.4%
5 204
11.3%
3 160
8.9%
4 147
8.1%
9 103
 
5.7%
6 101
 
5.6%
7 97
 
5.4%
8 92
 
5.1%
Other Punctuation
ValueCountFrequency (%)
. 6
85.7%
' 1
 
14.3%
Space Separator
ValueCountFrequency (%)
1034
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 82
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 5559
65.5%
Common 2927
34.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 983
17.7%
t 688
12.4%
n 415
 
7.5%
r 365
 
6.6%
a 330
 
5.9%
u 254
 
4.6%
o 239
 
4.3%
v 239
 
4.3%
s 231
 
4.2%
A 218
 
3.9%
Other values (36) 1597
28.7%
Common
ValueCountFrequency (%)
1034
35.3%
0 354
 
12.1%
1 340
 
11.6%
2 206
 
7.0%
5 204
 
7.0%
3 160
 
5.5%
4 147
 
5.0%
9 103
 
3.5%
6 101
 
3.5%
7 97
 
3.3%
Other values (4) 181
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8486
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1034
 
12.2%
e 983
 
11.6%
t 688
 
8.1%
n 415
 
4.9%
r 365
 
4.3%
0 354
 
4.2%
1 340
 
4.0%
a 330
 
3.9%
u 254
 
3.0%
o 239
 
2.8%
Other values (50) 3484
41.1%

city
Text

Distinct27
Distinct (%)6.1%
Missing0
Missing (%)0.0%
Memory size28.1 KiB
2023-12-09T22:09:41.381804image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length19
Median length16
Mean length8.140909091
Min length5

Characters and Unicode

Total characters3582
Distinct characters41
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10 ?
Unique (%)2.3%

Sample

1st rowManhattan
2nd rowBrooklyn
3rd rowBronx
4th rowBrooklyn
5th rowSouth Ozone Park
ValueCountFrequency (%)
brooklyn 124
24.5%
bronx 118
23.3%
manhattan 108
21.3%
island 22
 
4.3%
jamaica 13
 
2.6%
long 12
 
2.4%
city 12
 
2.4%
staten 10
 
2.0%
flushing 8
 
1.6%
park 8
 
1.6%
Other values (26) 72
14.2%
2023-12-09T22:09:41.752368image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
n 531
14.8%
a 450
12.6%
o 411
11.5%
r 285
 
8.0%
t 269
 
7.5%
B 244
 
6.8%
l 183
 
5.1%
y 144
 
4.0%
k 140
 
3.9%
h 132
 
3.7%
Other values (31) 793
22.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 3008
84.0%
Uppercase Letter 507
 
14.2%
Space Separator 67
 
1.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n 531
17.7%
a 450
15.0%
o 411
13.7%
r 285
9.5%
t 269
8.9%
l 183
 
6.1%
y 144
 
4.8%
k 140
 
4.7%
h 132
 
4.4%
x 118
 
3.9%
Other values (13) 345
11.5%
Uppercase Letter
ValueCountFrequency (%)
B 244
48.1%
M 111
21.9%
I 22
 
4.3%
F 17
 
3.4%
C 17
 
3.4%
S 17
 
3.4%
J 13
 
2.6%
L 12
 
2.4%
R 10
 
2.0%
H 10
 
2.0%
Other values (7) 34
 
6.7%
Space Separator
ValueCountFrequency (%)
67
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 3515
98.1%
Common 67
 
1.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
n 531
15.1%
a 450
12.8%
o 411
11.7%
r 285
 
8.1%
t 269
 
7.7%
B 244
 
6.9%
l 183
 
5.2%
y 144
 
4.1%
k 140
 
4.0%
h 132
 
3.8%
Other values (30) 726
20.7%
Common
ValueCountFrequency (%)
67
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3582
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n 531
14.8%
a 450
12.6%
o 411
11.5%
r 285
 
8.0%
t 269
 
7.5%
B 244
 
6.8%
l 183
 
5.1%
y 144
 
4.0%
k 140
 
3.9%
h 132
 
3.7%
Other values (31) 793
22.1%

zip
Text

Distinct119
Distinct (%)27.0%
Missing0
Missing (%)0.0%
Memory size26.8 KiB
2023-12-09T22:09:42.143507image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length5
Median length5
Mean length5
Min length5

Characters and Unicode

Total characters2200
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique36 ?
Unique (%)8.2%

Sample

1st row10003
2nd row11224
3rd row10473
4th row11225
5th row11420
ValueCountFrequency (%)
10457 13
 
3.0%
11101 12
 
2.7%
11201 11
 
2.5%
10002 11
 
2.5%
10019 11
 
2.5%
10456 11
 
2.5%
10468 10
 
2.3%
10473 9
 
2.0%
10451 9
 
2.0%
10458 9
 
2.0%
Other values (109) 334
75.9%
2023-12-09T22:09:42.658284image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 815
37.0%
0 459
20.9%
2 217
 
9.9%
4 192
 
8.7%
3 156
 
7.1%
6 115
 
5.2%
5 100
 
4.5%
7 67
 
3.0%
8 40
 
1.8%
9 39
 
1.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2200
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 815
37.0%
0 459
20.9%
2 217
 
9.9%
4 192
 
8.7%
3 156
 
7.1%
6 115
 
5.2%
5 100
 
4.5%
7 67
 
3.0%
8 40
 
1.8%
9 39
 
1.8%

Most occurring scripts

ValueCountFrequency (%)
Common 2200
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 815
37.0%
0 459
20.9%
2 217
 
9.9%
4 192
 
8.7%
3 156
 
7.1%
6 115
 
5.2%
5 100
 
4.5%
7 67
 
3.0%
8 40
 
1.8%
9 39
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2200
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 815
37.0%
0 459
20.9%
2 217
 
9.9%
4 192
 
8.7%
3 156
 
7.1%
6 115
 
5.2%
5 100
 
4.5%
7 67
 
3.0%
8 40
 
1.8%
9 39
 
1.8%

state_code
Text

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size25.5 KiB
2023-12-09T22:09:42.781318image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters880
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNY
2nd rowNY
3rd rowNY
4th rowNY
5th rowNY
ValueCountFrequency (%)
ny 440
100.0%
2023-12-09T22:09:42.992814image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 440
50.0%
Y 440
50.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 880
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N 440
50.0%
Y 440
50.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 880
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 440
50.0%
Y 440
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 880
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 440
50.0%
Y 440
50.0%

latitude
Text

Distinct252
Distinct (%)57.7%
Missing3
Missing (%)0.7%
Memory size27.9 KiB
2023-12-09T22:09:43.407374image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length8
Median length8
Mean length7.917620137
Min length6

Characters and Unicode

Total characters3460
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique170 ?
Unique (%)38.9%

Sample

1st row40.73653
2nd row40.57698
3rd row40.81504
4th row40.66981
5th row40.67502
ValueCountFrequency (%)
40.83931 6
 
1.4%
40.85947 6
 
1.4%
40.87517 6
 
1.4%
40.82122 6
 
1.4%
40.83978 6
 
1.4%
40.83251 6
 
1.4%
40.86044 5
 
1.1%
40.693 5
 
1.1%
40.86906 5
 
1.1%
40.74341 5
 
1.1%
Other values (242) 381
87.2%
2023-12-09T22:09:43.967713image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 646
18.7%
0 540
15.6%
. 437
12.6%
7 326
9.4%
6 318
9.2%
8 292
8.4%
5 202
 
5.8%
3 198
 
5.7%
1 188
 
5.4%
9 185
 
5.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3023
87.4%
Other Punctuation 437
 
12.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 646
21.4%
0 540
17.9%
7 326
10.8%
6 318
10.5%
8 292
9.7%
5 202
 
6.7%
3 198
 
6.5%
1 188
 
6.2%
9 185
 
6.1%
2 128
 
4.2%
Other Punctuation
ValueCountFrequency (%)
. 437
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3460
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
4 646
18.7%
0 540
15.6%
. 437
12.6%
7 326
9.4%
6 318
9.2%
8 292
8.4%
5 202
 
5.8%
3 198
 
5.7%
1 188
 
5.4%
9 185
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3460
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 646
18.7%
0 540
15.6%
. 437
12.6%
7 326
9.4%
6 318
9.2%
8 292
8.4%
5 202
 
5.8%
3 198
 
5.7%
1 188
 
5.4%
9 185
 
5.3%

longitude
Text

Distinct241
Distinct (%)55.0%
Missing2
Missing (%)0.5%
Memory size28.0 KiB
2023-12-09T22:09:44.404970image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length8
Median length8
Mean length7.915525114
Min length6

Characters and Unicode

Total characters3467
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique154 ?
Unique (%)35.2%

Sample

1st row-73.9927
2nd row-73.9854
3rd row-73.8561
4th row-73.9607
5th row-73.8167
ValueCountFrequency (%)
73.9927 6
 
1.4%
73.8616 6
 
1.4%
73.8396 6
 
1.4%
73.9114 6
 
1.4%
73.8559 6
 
1.4%
73.8782 6
 
1.4%
73.8886 6
 
1.4%
73.8693 5
 
1.1%
73.9572 5
 
1.1%
73.9863 5
 
1.1%
Other values (231) 381
87.0%
2023-12-09T22:09:44.971856image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7 596
17.2%
3 546
15.7%
- 438
12.6%
. 438
12.6%
9 398
11.5%
8 276
8.0%
1 151
 
4.4%
5 135
 
3.9%
2 132
 
3.8%
6 132
 
3.8%
Other values (2) 225
 
6.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2591
74.7%
Dash Punctuation 438
 
12.6%
Other Punctuation 438
 
12.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
7 596
23.0%
3 546
21.1%
9 398
15.4%
8 276
10.7%
1 151
 
5.8%
5 135
 
5.2%
2 132
 
5.1%
6 132
 
5.1%
4 128
 
4.9%
0 97
 
3.7%
Dash Punctuation
ValueCountFrequency (%)
- 438
100.0%
Other Punctuation
ValueCountFrequency (%)
. 438
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3467
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
7 596
17.2%
3 546
15.7%
- 438
12.6%
. 438
12.6%
9 398
11.5%
8 276
8.0%
1 151
 
4.4%
5 135
 
3.9%
2 132
 
3.8%
6 132
 
3.8%
Other values (2) 225
 
6.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3467
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7 596
17.2%
3 546
15.7%
- 438
12.6%
. 438
12.6%
9 398
11.5%
8 276
8.0%
1 151
 
4.4%
5 135
 
3.9%
2 132
 
3.8%
6 132
 
3.8%
Other values (2) 225
 
6.5%

community_board
Text

Distinct18
Distinct (%)4.1%
Missing1
Missing (%)0.2%
Memory size25.1 KiB
2023-12-09T22:09:45.170579image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.275626424
Min length1

Characters and Unicode

Total characters560
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row5
2nd row13
3rd row9
4th row9
5th row10
ValueCountFrequency (%)
1 48
10.9%
4 44
10.0%
3 41
9.3%
2 36
 
8.2%
9 34
 
7.7%
6 32
 
7.3%
12 31
 
7.1%
5 29
 
6.6%
8 28
 
6.4%
7 26
 
5.9%
Other values (8) 90
20.5%
2023-12-09T22:09:45.496517image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 189
33.8%
2 67
 
12.0%
4 58
 
10.4%
3 58
 
10.4%
6 37
 
6.6%
8 35
 
6.2%
9 34
 
6.1%
5 33
 
5.9%
7 30
 
5.4%
0 19
 
3.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 560
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 189
33.8%
2 67
 
12.0%
4 58
 
10.4%
3 58
 
10.4%
6 37
 
6.6%
8 35
 
6.2%
9 34
 
6.1%
5 33
 
5.9%
7 30
 
5.4%
0 19
 
3.4%

Most occurring scripts

ValueCountFrequency (%)
Common 560
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 189
33.8%
2 67
 
12.0%
4 58
 
10.4%
3 58
 
10.4%
6 37
 
6.6%
8 35
 
6.2%
9 34
 
6.1%
5 33
 
5.9%
7 30
 
5.4%
0 19
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 560
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 189
33.8%
2 67
 
12.0%
4 58
 
10.4%
3 58
 
10.4%
6 37
 
6.6%
8 35
 
6.2%
9 34
 
6.1%
5 33
 
5.9%
7 30
 
5.4%
0 19
 
3.4%

council_district
Text

Distinct51
Distinct (%)11.6%
Missing1
Missing (%)0.2%
Memory size25.3 KiB
2023-12-09T22:09:45.744790image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length2
Mean length1.758542141
Min length1

Characters and Unicode

Total characters772
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)0.5%

Sample

1st row2
2nd row47
3rd row18
4th row35
5th row28
ValueCountFrequency (%)
3 24
 
5.5%
33 21
 
4.8%
1 20
 
4.6%
17 20
 
4.6%
16 20
 
4.6%
2 17
 
3.9%
26 16
 
3.6%
15 14
 
3.2%
8 14
 
3.2%
18 14
 
3.2%
Other values (41) 259
59.0%
2023-12-09T22:09:46.121037image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 171
22.2%
3 147
19.0%
2 108
14.0%
4 91
11.8%
6 60
 
7.8%
7 54
 
7.0%
5 45
 
5.8%
8 40
 
5.2%
0 33
 
4.3%
9 23
 
3.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 772
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 171
22.2%
3 147
19.0%
2 108
14.0%
4 91
11.8%
6 60
 
7.8%
7 54
 
7.0%
5 45
 
5.8%
8 40
 
5.2%
0 33
 
4.3%
9 23
 
3.0%

Most occurring scripts

ValueCountFrequency (%)
Common 772
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 171
22.2%
3 147
19.0%
2 108
14.0%
4 91
11.8%
6 60
 
7.8%
7 54
 
7.0%
5 45
 
5.8%
8 40
 
5.2%
0 33
 
4.3%
9 23
 
3.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 772
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 171
22.2%
3 147
19.0%
2 108
14.0%
4 91
11.8%
6 60
 
7.8%
7 54
 
7.0%
5 45
 
5.8%
8 40
 
5.2%
0 33
 
4.3%
9 23
 
3.0%

census_tract
Text

Distinct207
Distinct (%)47.2%
Missing1
Missing (%)0.2%
Memory size25.9 KiB
2023-12-09T22:09:46.640634image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length6
Median length3
Mean length2.977220957
Min length1

Characters and Unicode

Total characters1307
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique113 ?
Unique (%)25.7%

Sample

1st row52
2nd row326
3rd row4
4th row213
5th row840
ValueCountFrequency (%)
409 10
 
2.3%
135 9
 
2.1%
194 7
 
1.6%
56 7
 
1.6%
16 7
 
1.6%
387 6
 
1.4%
213 6
 
1.4%
89 6
 
1.4%
179 6
 
1.4%
151 6
 
1.4%
Other values (197) 369
84.1%
2023-12-09T22:09:47.279170image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 262
20.0%
3 156
11.9%
2 145
11.1%
0 128
9.8%
5 122
9.3%
9 121
9.3%
4 107
8.2%
7 96
 
7.3%
6 88
 
6.7%
8 82
 
6.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1307
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 262
20.0%
3 156
11.9%
2 145
11.1%
0 128
9.8%
5 122
9.3%
9 121
9.3%
4 107
8.2%
7 96
 
7.3%
6 88
 
6.7%
8 82
 
6.3%

Most occurring scripts

ValueCountFrequency (%)
Common 1307
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 262
20.0%
3 156
11.9%
2 145
11.1%
0 128
9.8%
5 122
9.3%
9 121
9.3%
4 107
8.2%
7 96
 
7.3%
6 88
 
6.7%
8 82
 
6.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1307
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 262
20.0%
3 156
11.9%
2 145
11.1%
0 128
9.8%
5 122
9.3%
9 121
9.3%
4 107
8.2%
7 96
 
7.3%
6 88
 
6.7%
8 82
 
6.3%

bin
Text

Distinct257
Distinct (%)58.7%
Missing2
Missing (%)0.5%
Memory size27.6 KiB
2023-12-09T22:09:47.711998image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters3066
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique173 ?
Unique (%)39.5%

Sample

1st row1089902
2nd row3329331
3rd row2020580
4th row3029686
5th row4253607
ValueCountFrequency (%)
2007806 6
 
1.4%
2022205 6
 
1.4%
2057045 6
 
1.4%
2011810 6
 
1.4%
2074045 6
 
1.4%
1005283 5
 
1.1%
2050179 5
 
1.1%
3336215 5
 
1.1%
1013096 5
 
1.1%
1017828 5
 
1.1%
Other values (247) 383
87.4%
2023-12-09T22:09:48.252063image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 595
19.4%
1 388
12.7%
3 382
12.5%
2 355
11.6%
4 322
10.5%
5 236
 
7.7%
8 220
 
7.2%
7 203
 
6.6%
6 203
 
6.6%
9 162
 
5.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3066
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 595
19.4%
1 388
12.7%
3 382
12.5%
2 355
11.6%
4 322
10.5%
5 236
 
7.7%
8 220
 
7.2%
7 203
 
6.6%
6 203
 
6.6%
9 162
 
5.3%

Most occurring scripts

ValueCountFrequency (%)
Common 3066
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 595
19.4%
1 388
12.7%
3 382
12.5%
2 355
11.6%
4 322
10.5%
5 236
 
7.7%
8 220
 
7.2%
7 203
 
6.6%
6 203
 
6.6%
9 162
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3066
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 595
19.4%
1 388
12.7%
3 382
12.5%
2 355
11.6%
4 322
10.5%
5 236
 
7.7%
8 220
 
7.2%
7 203
 
6.6%
6 203
 
6.6%
9 162
 
5.3%

bbl
Text

Distinct256
Distinct (%)58.4%
Missing2
Missing (%)0.5%
Memory size28.8 KiB
2023-12-09T22:09:48.556548image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters4380
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique172 ?
Unique (%)39.3%

Sample

1st row1008420034
2nd row3070200039
3rd row2034780018
4th row3011870001
5th row4117140100
ValueCountFrequency (%)
2036040039 6
 
1.4%
2030590001 6
 
1.4%
2053680001 6
 
1.4%
2046330040 6
 
1.4%
2028170002 6
 
1.4%
3040940001 5
 
1.1%
2043580001 5
 
1.1%
1010790029 5
 
1.1%
2032470070 5
 
1.1%
1011570025 5
 
1.1%
Other values (246) 383
87.4%
2023-12-09T22:09:48.966239image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1796
41.0%
1 625
 
14.3%
2 409
 
9.3%
3 383
 
8.7%
4 292
 
6.7%
5 199
 
4.5%
8 183
 
4.2%
6 175
 
4.0%
7 165
 
3.8%
9 153
 
3.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4380
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1796
41.0%
1 625
 
14.3%
2 409
 
9.3%
3 383
 
8.7%
4 292
 
6.7%
5 199
 
4.5%
8 183
 
4.2%
6 175
 
4.0%
7 165
 
3.8%
9 153
 
3.5%

Most occurring scripts

ValueCountFrequency (%)
Common 4380
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1796
41.0%
1 625
 
14.3%
2 409
 
9.3%
3 383
 
8.7%
4 292
 
6.7%
5 199
 
4.5%
8 183
 
4.2%
6 175
 
4.0%
7 165
 
3.8%
9 153
 
3.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4380
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1796
41.0%
1 625
 
14.3%
2 409
 
9.3%
3 383
 
8.7%
4 292
 
6.7%
5 199
 
4.5%
8 183
 
4.2%
6 175
 
4.0%
7 165
 
3.8%
9 153
 
3.5%

nta
Text

Distinct119
Distinct (%)27.1%
Missing1
Missing (%)0.2%
Memory size56.7 KiB
2023-12-09T22:09:49.226762image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length75
Median length75
Mean length75
Min length75

Characters and Unicode

Total characters32925
Distinct characters55
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique35 ?
Unique (%)8.0%

Sample

1st rowHudson Yards-Chelsea-Flatiron-Union Square
2nd rowSeagate-Coney Island
3rd rowSoundview-Castle Hill-Clason Point-Harding Park
4th rowCrown Heights South
5th rowSouth Ozone Park
ValueCountFrequency (%)
east 42
 
4.1%
park 37
 
3.6%
north 34
 
3.3%
heights 29
 
2.8%
village 27
 
2.7%
south 26
 
2.6%
hill 25
 
2.5%
west 20
 
2.0%
square 18
 
1.8%
hills 15
 
1.5%
Other values (165) 745
73.2%
2023-12-09T22:09:49.598095image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
24210
73.5%
e 718
 
2.2%
a 657
 
2.0%
o 640
 
1.9%
r 608
 
1.8%
n 602
 
1.8%
l 561
 
1.7%
t 555
 
1.7%
i 527
 
1.6%
s 446
 
1.4%
Other values (45) 3401
 
10.3%

Most occurring categories

ValueCountFrequency (%)
Space Separator 24210
73.5%
Lowercase Letter 7008
 
21.3%
Uppercase Letter 1376
 
4.2%
Dash Punctuation 317
 
1.0%
Open Punctuation 5
 
< 0.1%
Close Punctuation 5
 
< 0.1%
Other Punctuation 4
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 718
10.2%
a 657
9.4%
o 640
9.1%
r 608
8.7%
n 602
8.6%
l 561
 
8.0%
t 555
 
7.9%
i 527
 
7.5%
s 446
 
6.4%
h 245
 
3.5%
Other values (15) 1449
20.7%
Uppercase Letter
ValueCountFrequency (%)
H 185
13.4%
C 162
11.8%
B 155
11.3%
S 121
 
8.8%
M 93
 
6.8%
P 90
 
6.5%
E 63
 
4.6%
N 61
 
4.4%
W 57
 
4.1%
V 55
 
4.0%
Other values (14) 334
24.3%
Other Punctuation
ValueCountFrequency (%)
. 3
75.0%
' 1
 
25.0%
Space Separator
ValueCountFrequency (%)
24210
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 317
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 24541
74.5%
Latin 8384
 
25.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 718
 
8.6%
a 657
 
7.8%
o 640
 
7.6%
r 608
 
7.3%
n 602
 
7.2%
l 561
 
6.7%
t 555
 
6.6%
i 527
 
6.3%
s 446
 
5.3%
h 245
 
2.9%
Other values (39) 2825
33.7%
Common
ValueCountFrequency (%)
24210
98.7%
- 317
 
1.3%
( 5
 
< 0.1%
) 5
 
< 0.1%
. 3
 
< 0.1%
' 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 32925
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
24210
73.5%
e 718
 
2.2%
a 657
 
2.0%
o 640
 
1.9%
r 608
 
1.8%
n 602
 
1.8%
l 561
 
1.7%
t 555
 
1.7%
i 527
 
1.6%
s 446
 
1.4%
Other values (45) 3401
 
10.3%

borough
Text

Distinct5
Distinct (%)1.1%
Missing1
Missing (%)0.2%
Memory size28.5 KiB
2023-12-09T22:09:49.776850image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length9
Median length9
Mean length9
Min length9

Characters and Unicode

Total characters3951
Distinct characters18
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowMANHATTAN
2nd rowBROOKLYN
3rd rowBRONX
4th rowBROOKLYN
5th rowQUEENS
ValueCountFrequency (%)
brooklyn 124
27.6%
bronx 118
26.3%
manhattan 107
23.8%
queens 80
17.8%
staten 10
 
2.2%
is 10
 
2.2%
2023-12-09T22:09:50.073593image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
846
21.4%
N 546
13.8%
O 366
9.3%
A 331
 
8.4%
B 242
 
6.1%
R 242
 
6.1%
T 234
 
5.9%
E 170
 
4.3%
K 124
 
3.1%
L 124
 
3.1%
Other values (8) 726
18.4%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 3105
78.6%
Space Separator 846
 
21.4%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N 546
17.6%
O 366
11.8%
A 331
10.7%
B 242
7.8%
R 242
7.8%
T 234
 
7.5%
E 170
 
5.5%
K 124
 
4.0%
L 124
 
4.0%
Y 124
 
4.0%
Other values (7) 602
19.4%
Space Separator
ValueCountFrequency (%)
846
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 3105
78.6%
Common 846
 
21.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 546
17.6%
O 366
11.8%
A 331
10.7%
B 242
7.8%
R 242
7.8%
T 234
 
7.5%
E 170
 
5.5%
K 124
 
4.0%
L 124
 
4.0%
Y 124
 
4.0%
Other values (7) 602
19.4%
Common
ValueCountFrequency (%)
846
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3951
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
846
21.4%
N 546
13.8%
O 366
9.3%
A 331
 
8.4%
B 242
 
6.1%
R 242
 
6.1%
T 234
 
5.9%
E 170
 
4.3%
K 124
 
3.1%
L 124
 
3.1%
Other values (8) 726
18.4%